A B C D E F G H I J K L M N O P Q R S T U V W X Y Z _

A

AbstractBin - Class in hex.tree.dt.binning

Single bin holding limits (min excluded), count of samples and count of class 0.

AbstractBin() - Constructor for class hex.tree.dt.binning.AbstractBin

AbstractCompressedNode - Class in hex.tree.dt

AbstractCompressedNode() - Constructor for class hex.tree.dt.AbstractCompressedNode

AbstractCompressedNode - Class in hex.tree.isoforextended.isolationtree

Upper class for CompressedNode and CompressedLeaf used to access both types from array.

AbstractCompressedNode(int) - Constructor for class hex.tree.isoforextended.isolationtree.AbstractCompressedNode

AbstractFeatureLimits - Class in hex.tree.dt

Limits for one feature.

AbstractFeatureLimits() - Constructor for class hex.tree.dt.AbstractFeatureLimits

AbstractSplittingRule - Class in hex.tree.dt

AbstractSplittingRule() - Constructor for class hex.tree.dt.AbstractSplittingRule

accumulateLeftStatistics(int, int) - Method in class hex.tree.dt.binning.SplitStatistics

accumulateRightStatistics(int, int) - Method in class hex.tree.dt.binning.SplitStatistics

accuracy(int) - Method in class hex.tree.drf.TreeMeasuresCollector.TreeMeasures

Returns a list of accuracies per tree.

accuracy() - Method in class hex.tree.drf.TreeMeasuresCollector.TreeMeasures

accuracy(int) - Method in class hex.tree.drf.TreeMeasuresCollector.TreeSSE

accuracy(int) - Method in class hex.tree.drf.TreeMeasuresCollector.TreeVotes

Returns accuracy per individual trees.

activation - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

The activation function (non-linearity) to be used by the neurons in the hidden layers.

activeBC() - Method in class hex.glm.ComputationState

activeCols() - Method in class hex.DataInfo

activeConstraints(ConstrainedGLMUtils.LinearConstraints[], ConstrainedGLMUtils.LinearConstraints[]) - Static method in class hex.glm.ConstrainedGLMUtils

activeData() - Method in class hex.glm.ComputationState

activeDataMultinomial() - Method in class hex.glm.ComputationState

activeDataMultinomial(int) - Method in class hex.glm.ComputationState

actNBins() - Method in class hex.tree.DHistogram

actual_best_model_key - Variable in class hex.deeplearning.DeepLearningModel

actual_mtries() - Method in class hex.tree.DTree

actual_train_samples_per_iteration - Variable in class hex.deeplearning.DeepLearningModel

AdaBoost - Class in hex.adaboost

Implementation of AdaBoost algorithm based on Raul Rojas, "Adaboost and the Super Bowl of Classifiers A Tutorial Introduction to Adaptive Boosting" Alexandru Niculescu-Mizil and Richard A.

AdaBoost(AdaBoostModel.AdaBoostParameters) - Constructor for class hex.adaboost.AdaBoost

AdaBoost(boolean) - Constructor for class hex.adaboost.AdaBoost

AdaBoostModel - Class in hex.adaboost

AdaBoostModel(Key<AdaBoostModel>, AdaBoostModel.AdaBoostParameters, AdaBoostModel.AdaBoostOutput) - Constructor for class hex.adaboost.AdaBoostModel

AdaBoostModel.AdaBoostOutput - Class in hex.adaboost

AdaBoostModel.AdaBoostParameters - Class in hex.adaboost

AdaBoostModel.Algorithm - Enum in hex.adaboost

AdaBoostModelOutputV3() - Constructor for class hex.schemas.AdaBoostModelV3.AdaBoostModelOutputV3

AdaBoostModelV3 - Class in hex.schemas

AdaBoostModelV3() - Constructor for class hex.schemas.AdaBoostModelV3

AdaBoostModelV3.AdaBoostModelOutputV3 - Class in hex.schemas

AdaBoostOutput(AdaBoost) - Constructor for class hex.adaboost.AdaBoostModel.AdaBoostOutput

AdaBoostParameters() - Constructor for class hex.adaboost.AdaBoostModel.AdaBoostParameters

AdaBoostParametersV3() - Constructor for class hex.schemas.AdaBoostV3.AdaBoostParametersV3

AdaBoostV3 - Class in hex.schemas

AdaBoostV3() - Constructor for class hex.schemas.AdaBoostV3

AdaBoostV3.AdaBoostParametersV3 - Class in hex.schemas

adaptFrameForScore(Frame, boolean) - Method in class hex.generic.GenericModel

adaptive_rate - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

The implemented adaptive learning rate algorithm (ADADELTA) automatically combines the benefits of learning rate annealing and momentum training to avoid slow convergence.

adaptTestForJavaScoring(Frame, boolean) - Method in class hex.coxph.CoxPHModel

adaptTestForTrain(Frame, boolean, boolean) - Method in class hex.coxph.CoxPHModel

adaptTestForTrain(Frame, boolean, boolean) - Method in class hex.gam.GAMModel

This method will massage the input training frame such that it can be used for scoring for a GAM model.

adaptTestForTrain(Frame, boolean, boolean) - Method in class hex.tree.isofor.IsolationForestModel

adaptValidFrame(Frame, Frame, GAMModel.GAMParameters, String[][], double[][][], double[][][], double[][][], double[][][], int[][][], double[][], double[][], int[]) - Static method in class hex.gam.GAMModel

add(int, int, double) - Method in class hex.coxph.Storage.DenseRowMatrix

add(int, int, double) - Method in interface hex.coxph.Storage.Matrix

add(DeepLearningModelInfo) - Method in class hex.deeplearning.DeepLearningModelInfo

Add another model info into this This will add the weights/biases/learning rate helpers, and the number of processed training samples Note: It will NOT add the elastic averaging helpers, which are always kept constant (they already are the result of a reduction)

add(int, int, float) - Method in class hex.deeplearning.Storage.DenseColMatrix

add(int, int, float) - Method in class hex.deeplearning.Storage.DenseRowMatrix

add(int, double) - Method in class hex.deeplearning.Storage.DenseVector

add(int, int, float) - Method in interface hex.deeplearning.Storage.Matrix

add(int, int, float) - Method in class hex.deeplearning.Storage.SparseRowMatrix

add(int, int, int, float) - Method in interface hex.deeplearning.Storage.Tensor

add(int, double) - Method in interface hex.deeplearning.Storage.Vector

add(double, double[], double, double) - Method in class hex.glm.GLMMetricBuilder

add(double, double, double, double) - Method in class hex.glm.GLMMetricBuilder

add(Gram) - Method in class hex.gram.Gram

add(DHistogram) - Method in class hex.tree.DHistogram

add(double[], double[]) - Static method in class hex.tree.FriedmanPopescusH

add_processed_global(long) - Method in class hex.deeplearning.DeepLearningModelInfo

add_processed_local(long) - Method in class hex.deeplearning.DeepLearningModelInfo

addBCEqualityConstraint(List<ConstrainedGLMUtils.LinearConstraints>, GLM.BetaConstraint, String[], int) - Static method in class hex.glm.ConstrainedGLMUtils

This method will extract the equality constraint and add to equalityC from beta constraint by doing the following transformation: val <= beta <= val: transformed to beta-val == 0, add to equalTo constraint.

addBCGreaterThanConstraint(List<ConstrainedGLMUtils.LinearConstraints>, GLM.BetaConstraint, String[], int) - Static method in class hex.glm.ConstrainedGLMUtils

This method will extract the greater than constraint and add to lessThanC from beta constraint by doing the following transformation: low_val <= beta <= Infinity: transformed to low_val - beta <= 0.

addBCLessThanConstraint(List<ConstrainedGLMUtils.LinearConstraints>, GLM.BetaConstraint, String[], int) - Static method in class hex.glm.ConstrainedGLMUtils

This method will extract the less than constraint and add to lessThanC from beta constraint by doing the following transformation: -Infinity <= beta <= high_val: transformed to beta - high_val <= 0.

addCols(double[], int[], int[], ComputationState.GramXY, double[][], double[]) - Static method in class hex.glm.ComputationState.GramXY

addConstraintGradient(double[], ConstrainedGLMUtils.ConstraintsDerivatives[], GLM.GLMGradientInfo) - Static method in class hex.glm.ConstrainedGLMUtils

Add contribution of constraints to objective/likelihood/gradient.

addConstraintObj(double[], ConstrainedGLMUtils.LinearConstraints[], double) - Static method in class hex.glm.ComputationState

This method adds to objective function the contribution of transpose(lambda)*constraint vector + ck/2*transpose(constraint vector)*constraint vector

addContribToNewChunk(float[], NewChunk[]) - Method in class hex.tree.drf.DRFModel.ScoreContributionsTaskDRF

addContribToNewChunk(float[], int[], NewChunk[]) - Method in class hex.tree.SharedTreeModelWithContributions.ScoreContributionsSortingTask

addContribToNewChunk(float[], NewChunk[]) - Method in class hex.tree.SharedTreeModelWithContributions.ScoreContributionsTask

addContribToNewChunk(double[], NewChunk[]) - Method in class hex.tree.SharedTreeModelWithContributions.ScoreContributionsWithBackgroundTask

AddCSGamColumns - Class in hex.gam.MatrixFrameUtils

Given a Frame, the class will generate all the gamified columns.

AddCSGamColumns(double[][][], double[][][], double[][][], int[], Frame, int[]) - Constructor for class hex.gam.MatrixFrameUtils.AddCSGamColumns

addCustomInfo(IsolationForestModel.IsolationForestOutput) - Method in class hex.tree.isofor.IsolationForest

addCustomInfo(O) - Method in class hex.tree.SharedTree

addCustomInfo(UpliftDRFModel.UpliftDRFOutput) - Method in class hex.tree.uplift.UpliftDRF

addDiag(double[]) - Method in class hex.gram.Gram

addDiag(double) - Method in class hex.gram.Gram

addDiag(double, boolean) - Method in class hex.gram.Gram

addExemplar(Aggregator.Exemplar[], Aggregator.Exemplar) - Static method in class hex.aggregator.Aggregator.Exemplar

Add a new exemplar to the input array (doubling it if necessary)

addGAMPenalty(Integer[], double[][][], int[][]) - Method in class hex.gram.Gram

Add the effect of gam column smoothness factor.

addGAMPenalty(double[][][], int[][], double[][]) - Method in class hex.gram.Gram

addIndividualPred(String[], List<String[]>) - Static method in class hex.anovaglm.ANOVAGLMUtils

AddISGamColumns - Class in hex.gam.MatrixFrameUtils

class to gamified all gam_columns with bs set to 2.

AddISGamColumns(double[][][], int[], int[], int[], Frame) - Constructor for class hex.gam.MatrixFrameUtils.AddISGamColumns

additionalParameters - Variable in class hex.schemas.GenericV3.GenericParametersV3

addKTrees(DTree[]) - Method in class hex.tree.SharedTreeModel.SharedTreeOutput

AddMSGamColumns - Class in hex.gam.MatrixFrameUtils

This task will gamified all gam predictors with bs=3.

AddMSGamColumns(double[][][], double[][][], int[], int[], int[], Frame) - Constructor for class hex.gam.MatrixFrameUtils.AddMSGamColumns

addNewPred2CPM(double[][], Frame, double[][], int[], int[][], boolean) - Static method in class hex.modelselection.ModelSelectionUtils

Given current CPM which has been swept already, we need to add the lastest predictor to the current CPM that have not been swept.

addNum(int, double) - Method in class hex.DataInfo.Row

addOffset2Cols(int[]) - Method in class hex.glm.ComputationState

addOneRow2ScoringHistory(TwoDimTable, TwoDimTable, int, int, int, int, int, boolean, boolean, List<Integer>, TwoDimTable, int) - Static method in class hex.glm.GLMUtils

addOutput(String, Vec) - Method in class hex.DataInfo

addPenaltyGradient(ConstrainedGLMUtils.ConstraintsDerivatives[], ConstrainedGLMUtils.LinearConstraints[], GLM.GLMGradientInfo, double) - Static method in class hex.glm.ConstrainedGLMUtils

This method adds the contribution to the gradient from the penalty term ck/2*transpose(h(beta))*h(beta)

addPermutationList(List<Integer[]>, List<List<Integer>>) - Static method in class hex.gam.GamSplines.ThinPlateRegressionUtils

addResponse(String[], Vec[]) - Method in class hex.DataInfo

addRow(DataInfo.Row, double) - Method in class hex.gram.Gram

addRowDense(DataInfo.Row, double) - Method in class hex.gram.Gram

addRowSparse(DataInfo.Row, double) - Method in class hex.gram.Gram

addScoringInfo(GLMModel.GLMParameters, int, long, int) - Method in class hex.glm.GLMModel

addSingleVariableGamColumns(Frame, GAMModel.GAMParameters, String[][], double[][][], double[][][], double[][][], int[]) - Static method in class hex.gam.GAMModel

addSubmodel(int, GLMModel.Submodel) - Method in class hex.glm.GLMModel

addToArray(double, double[]) - Method in class hex.DataInfo.Row

addTPGamCols(double[][], double[][]) - Method in class hex.gam.MatrixFrameUtils.AddTPKnotsGamColumns

addTPGamColumns(Frame, GAMModel.GAMParameters, double[][][], double[][][], int[][][], double[][][], double[][], double[][]) - Static method in class hex.gam.GAMModel

AddTPKnotsGamColumns - Class in hex.gam.MatrixFrameUtils

AddTPKnotsGamColumns(GAMModel.GAMParameters, double[][][], double[][][], int[][][], double[][][], Frame) - Constructor for class hex.gam.MatrixFrameUtils.AddTPKnotsGamColumns

AddTPKnotsGamColumns.ApplyTPRegressionSmootherWithKnots - Class in hex.gam.MatrixFrameUtils

adjustGradient(double[], double[]) - Method in class hex.glm.GLM.BetaConstraint

adjustLambda(ConstrainedGLMUtils.LinearConstraints[], double[]) - Static method in class hex.glm.ConstrainedGLMUtils

ADMM - Class in hex.optimization

Created by tomasnykodym on 3/2/15.

ADMM() - Constructor for class hex.optimization.ADMM

ADMM.L1Solver - Class in hex.optimization

ADMM.ProximalSolver - Interface in hex.optimization

aggregate_method - Variable in class hex.schemas.Word2VecTransformV3

Aggregator - Class in hex.aggregator

Aggregator(AggregatorModel.AggregatorParameters) - Constructor for class hex.aggregator.Aggregator

Aggregator(boolean) - Constructor for class hex.aggregator.Aggregator

Aggregator.Exemplar - Class in hex.aggregator

AggregatorModel - Class in hex.aggregator

AggregatorModel(Key, AggregatorModel.AggregatorParameters, AggregatorModel.AggregatorOutput) - Constructor for class hex.aggregator.AggregatorModel

AggregatorModel.AggregatorOutput - Class in hex.aggregator

AggregatorModel.AggregatorParameters - Class in hex.aggregator

AggregatorModelMetrics(int) - Constructor for class hex.aggregator.ModelMetricsAggregator.AggregatorModelMetrics

AggregatorModelOutputV99() - Constructor for class hex.schemas.AggregatorModelV99.AggregatorModelOutputV99

AggregatorModelV99 - Class in hex.schemas

AggregatorModelV99() - Constructor for class hex.schemas.AggregatorModelV99

AggregatorModelV99.AggregatorModelOutputV99 - Class in hex.schemas

AggregatorOutput(Aggregator) - Constructor for class hex.aggregator.AggregatorModel.AggregatorOutput

AggregatorParameters() - Constructor for class hex.aggregator.AggregatorModel.AggregatorParameters

AggregatorParametersV99() - Constructor for class hex.schemas.AggregatorV99.AggregatorParametersV99

AggregatorV99 - Class in hex.schemas

AggregatorV99() - Constructor for class hex.schemas.AggregatorV99

AggregatorV99.AggregatorParametersV99 - Class in hex.schemas

aic(double) - Method in class hex.generic.GenericModel

algoName() - Method in class hex.adaboost.AdaBoostModel.AdaBoostParameters

algoName() - Method in class hex.aggregator.AggregatorModel.AggregatorParameters

algoName() - Method in class hex.anovaglm.ANOVAGLMModel.ANOVAGLMParameters

algoName() - Method in class hex.coxph.CoxPHModel.CoxPHParameters

algoName() - Method in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

algoName() - Method in class hex.ensemble.StackedEnsembleModel.StackedEnsembleParameters

algoName() - Method in class hex.gam.GAMModel.GAMParameters

algoName() - Method in class hex.generic.GenericModelParameters

algoName() - Method in class hex.glm.GLMModel.GLMParameters

algoName() - Method in class hex.glrm.GLRMModel.GLRMParameters

algoName() - Method in class hex.grep.GrepModel.GrepParameters

algoName() - Method in class hex.hglm.HGLMModel.HGLMParameters

algoName() - Method in class hex.isotonic.IsotonicRegressionModel.IsotonicRegressionParameters

algoName() - Method in class hex.kmeans.KMeansModel.KMeansParameters

algoName() - Method in class hex.modelselection.ModelSelectionModel.ModelSelectionParameters

algoName() - Method in class hex.naivebayes.NaiveBayesModel.NaiveBayesParameters

algoName() - Method in class hex.pca.PCAModel.PCAParameters

algoName() - Method in class hex.psvm.PSVMModel.PSVMParameters

algoName() - Method in class hex.rulefit.RuleFitModel.RuleFitParameters

algoName() - Method in class hex.svd.SVDModel.SVDParameters

algoName() - Method in class hex.tree.drf.DRFModel.DRFParameters

algoName() - Method in class hex.tree.dt.DTModel.DTParameters

algoName() - Method in class hex.tree.gbm.GBMModel.GBMParameters

algoName() - Method in class hex.tree.isofor.IsolationForestModel.IsolationForestParameters

algoName() - Method in class hex.tree.isoforextended.ExtendedIsolationForestModel.ExtendedIsolationForestParameters

algoName() - Method in class hex.tree.uplift.UpliftDRFModel.UpliftDRFParameters

algoName() - Method in class hex.word2vec.Word2VecModel.Word2VecParameters

algorithm - Variable in class hex.schemas.RuleFitV3.RuleFitParametersV3

AlgorithmValuesProvider() - Constructor for class hex.schemas.StackedEnsembleV99.StackedEnsembleParametersV99.AlgorithmValuesProvider

allocate2DArray(GamUtils.AllocateType, int) - Static method in class hex.gam.MatrixFrameUtils.GamUtils

allocate3DArray(int, GAMModel.GAMParameters, GamUtils.AllocateType) - Static method in class hex.gam.MatrixFrameUtils.GamUtils

allocate3DArrayCS(int, GAMModel.GAMParameters, GamUtils.AllocateType) - Static method in class hex.gam.MatrixFrameUtils.GamUtils

allocate3DArrayTP(int, GAMModel.GAMParameters, int[], int[]) - Static method in class hex.gam.MatrixFrameUtils.GamUtils

allocateRow(int[]) - Static method in class hex.anovaglm.GenerateTransformColumns

allowedInteractionContainsColumn(int) - Method in class hex.tree.GlobalInteractionConstraints

alpha() - Method in class hex.glm.ComputationState

alpha - Variable in class hex.schemas.ANOVAGLMV3.ANOVAGLMParametersV3

alpha - Variable in class hex.schemas.GAMV3.GAMParametersV3

alpha - Variable in class hex.schemas.GLMV3.GLMParametersV3

alpha - Variable in class hex.schemas.ModelSelectionV3.ModelSelectionParametersV3

alpha_best() - Method in class hex.glm.GLMModel.GLMOutput

alpha_key - Variable in class hex.schemas.PSVMModelV3.PSVMModelOutputV3

alpha_value - Variable in class hex.glm.GLMModel.Submodel

alphas - Variable in class hex.adaboost.AdaBoostModel.AdaBoostOutput

alphas - Variable in class hex.schemas.GLMRegularizationPathV3

ANOVAGLM - Class in hex.anovaglm

ANOVAGLM(boolean) - Constructor for class hex.anovaglm.ANOVAGLM

ANOVAGLM(ANOVAGLMModel.ANOVAGLMParameters) - Constructor for class hex.anovaglm.ANOVAGLM

ANOVAGLM(ANOVAGLMModel.ANOVAGLMParameters, Key<ANOVAGLMModel>) - Constructor for class hex.anovaglm.ANOVAGLM

ANOVAGLMModel - Class in hex.anovaglm

ANOVAGLMModel(Key<ANOVAGLMModel>, ANOVAGLMModel.ANOVAGLMParameters, ANOVAGLMModel.ANOVAGLMModelOutput) - Constructor for class hex.anovaglm.ANOVAGLMModel

ANOVAGLMModel.ANOVAGLMModelOutput - Class in hex.anovaglm

ANOVAGLMModel.ANOVAGLMParameters - Class in hex.anovaglm

ANOVAGLMModelOutput(ANOVAGLM, DataInfo) - Constructor for class hex.anovaglm.ANOVAGLMModel.ANOVAGLMModelOutput

ANOVAGLMModelOutputV3() - Constructor for class hex.schemas.ANOVAGLMModelV3.ANOVAGLMModelOutputV3

ANOVAGLMModelV3 - Class in hex.schemas

ANOVAGLMModelV3() - Constructor for class hex.schemas.ANOVAGLMModelV3

ANOVAGLMModelV3.ANOVAGLMModelOutputV3 - Class in hex.schemas

ANOVAGLMParameters() - Constructor for class hex.anovaglm.ANOVAGLMModel.ANOVAGLMParameters

ANOVAGLMParametersV3() - Constructor for class hex.schemas.ANOVAGLMV3.ANOVAGLMParametersV3

ANOVAGLMUtils - Class in hex.anovaglm

ANOVAGLMUtils() - Constructor for class hex.anovaglm.ANOVAGLMUtils

ANOVAGLMV3 - Class in hex.schemas

ANOVAGLMV3() - Constructor for class hex.schemas.ANOVAGLMV3

ANOVAGLMV3.ANOVAGLMParametersV3 - Class in hex.schemas

append(T) - Method in class hex.tree.drf.TreeMeasuresCollector.TreeMeasures

append(TreeMeasuresCollector.TreeSSE) - Method in class hex.tree.drf.TreeMeasuresCollector.TreeSSE

append(float, double) - Method in class hex.tree.drf.TreeMeasuresCollector.TreeSSE

Append a tree sse to a list of trees.

append(double, double) - Method in class hex.tree.drf.TreeMeasuresCollector.TreeVotes

Append a tree votes to a list of trees.

append(TreeMeasuresCollector.TreeVotes) - Method in class hex.tree.drf.TreeMeasuresCollector.TreeVotes

appendToStringMetrics(StringBuilder) - Method in class hex.tree.isofor.ModelMetricsAnomaly

apply(Env, Env.StackHelp, AstRoot[]) - Method in class water.rapids.prims.AstPredictedVsActualByVar

apply(Env, Env.StackHelp, AstRoot[]) - Method in class water.rapids.prims.AstSetCalibrationModel

apply(Env, Env.StackHelp, AstRoot[]) - Method in class water.rapids.prims.isotonic.AstPoolAdjacentViolators

apply(Env, Env.StackHelp, AstRoot[]) - Method in class water.rapids.prims.rulefit.AstPredictRule

apply(Env, Env.StackHelp, AstRoot[]) - Method in class water.rapids.prims.tree.AstTreeUpdateWeights

apply(Env, Env.StackHelp, AstRoot[]) - Method in class water.rapids.prims.word2vec.AstWord2VecToFrame

applyAllBounds(double[]) - Method in class hex.glm.GLM.BetaConstraint

applyBounds(double, int) - Method in class hex.glm.GLM.BetaConstraint

applyGramSchmit(double[][]) - Static method in class hex.util.LinearAlgebraUtils

applyStrongRules(double, double) - Method in class hex.glm.ComputationState

Apply strong rules to filter out expected inactive (with zero coefficient) predictors.

applyStrongRulesMultinomial(double, double) - Method in class hex.glm.ComputationState

Apply strong rules to filter out expected inactive (with zero coefficient) predictors.

applyStrongRulesMultinomial_old(double, double) - Method in class hex.glm.ComputationState

Apply strong rules to filter out expected inactive (with zero coefficient) predictors.

applySweepVectors2NewPred(ModelSelectionUtils.SweepVector[][], double[][], int, int[]) - Static method in class hex.modelselection.ModelSelectionUtils

This method will sweep the rows/columns added to the CPM due to the addition of the new predictor using sweep vector arrays.

ApplyTPRegressionSmootherWithKnots(Frame, GAMModel.GAMParameters, int, double[][], int, double[][], double[][], int[][], double[], double[]) - Constructor for class hex.gam.MatrixFrameUtils.AddTPKnotsGamColumns.ApplyTPRegressionSmootherWithKnots

applyTransform(Frame, String, GAMModel.GAMParameters, double[][], int) - Static method in class hex.gam.GamSplines.ThinPlateDistanceWithKnots

This function perform the operation described in 3.3 regarding the part of data Xnmd.

apriori - Variable in class hex.schemas.NaiveBayesModelV3.NaiveBayesModelOutputV3

archetypes - Variable in class hex.schemas.GLRMModelV3.GLRMModelOutputV3

args() - Method in class water.rapids.prims.AstPredictedVsActualByVar

args() - Method in class water.rapids.prims.AstSetCalibrationModel

args() - Method in class water.rapids.prims.isotonic.AstPoolAdjacentViolators

args() - Method in class water.rapids.prims.rulefit.AstPredictRule

args() - Method in class water.rapids.prims.tree.AstTreeUpdateWeights

args() - Method in class water.rapids.prims.word2vec.AstWord2VecToFrame

assertValidGAMColumnsCountSplineTypes() - Method in class hex.gam.GAM

Check and make sure correct BS type is assigned to the various gam_columns specified.

asSSE(TreeMeasuresCollector.TreeMeasures) - Static method in class hex.tree.drf.TreeMeasuresCollector

AstPoolAdjacentViolators - Class in water.rapids.prims.isotonic

AstPoolAdjacentViolators() - Constructor for class water.rapids.prims.isotonic.AstPoolAdjacentViolators

AstPredictedVsActualByVar - Class in water.rapids.prims

AstPredictedVsActualByVar() - Constructor for class water.rapids.prims.AstPredictedVsActualByVar

AstPredictRule - Class in water.rapids.prims.rulefit

Evaluates validity of the given rules on the given data.

AstPredictRule() - Constructor for class water.rapids.prims.rulefit.AstPredictRule

AstSetCalibrationModel - Class in water.rapids.prims

AstSetCalibrationModel() - Constructor for class water.rapids.prims.AstSetCalibrationModel

AstTreeUpdateWeights - Class in water.rapids.prims.tree

Re-weights auxiliary trees in a TreeModel

AstTreeUpdateWeights() - Constructor for class water.rapids.prims.tree.AstTreeUpdateWeights

AstWord2VecToFrame - Class in water.rapids.prims.word2vec

Converts a word2vec model to a Frame

AstWord2VecToFrame() - Constructor for class water.rapids.prims.word2vec.AstWord2VecToFrame

asVotes(TreeMeasuresCollector.TreeMeasures) - Static method in class hex.tree.drf.TreeMeasuresCollector

auto_rebalance - Variable in class hex.schemas.GBMV3.GBMParametersV3

autoencoder - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

autoEncoderGradient(int, int) - Method in class hex.deeplearning.Neurons

Helper to compute the reconstruction error for auto-encoders (part of the gradient computation)

auuc_nbins - Variable in class hex.schemas.UpliftDRFV3.UpliftDRFParametersV3

auuc_type - Variable in class hex.schemas.UpliftDRFV3.UpliftDRFParametersV3

average_activation - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

avg_change_obj - Variable in class hex.schemas.GLRMModelV3.GLRMModelOutputV3

B

backwardSolve(double[][], double[], double[]) - Static method in class hex.util.LinearAlgebraUtils

balance_classes - Variable in class hex.schemas.ANOVAGLMV3.ANOVAGLMParametersV3

For imbalanced data, balance training data class counts via over/under-sampling.

balance_classes - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

For imbalanced data, balance training data class counts via over/under-sampling.

balance_classes - Variable in class hex.schemas.GAMV3.GAMParametersV3

For imbalanced data, balance training data class counts via over/under-sampling.

balance_classes - Variable in class hex.schemas.GLMV3.GLMParametersV3

For imbalanced data, balance training data class counts via over/under-sampling.

balance_classes - Variable in class hex.schemas.ModelSelectionV3.ModelSelectionParametersV3

For imbalanced data, balance training data class counts via over/under-sampling.

balance_classes - Variable in class hex.schemas.NaiveBayesV3.NaiveBayesParametersV3

For imbalanced data, balance training data class counts via over/under-sampling.

balance_classes - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3

For imbalanced data, balance training data class counts via over/under-sampling.

base_models - Variable in class hex.schemas.StackedEnsembleV99.StackedEnsembleParametersV99

bestCol(DTree.UndecidedNode, DHistogram[], Constraints) - Method in class hex.tree.DTree.DecidedNode

bestSubmodel() - Method in class hex.glm.GLMModel.GLMOutput

bestSubmodelIndex() - Method in class hex.glm.GLMModel.GLMOutput

beta() - Method in class hex.glm.ComputationState

beta - Variable in class hex.glm.ComputationState.GramGrad

beta() - Method in class hex.glm.GLMModel

beta(double) - Method in class hex.glm.GLMModel

beta() - Method in class hex.glm.GLMModel.GLMOutput

beta - Variable in class hex.glm.GLMModel.Submodel

beta() - Method in class hex.modelselection.ModelSelectionModel.ModelSelectionModelOutput

beta - Variable in class hex.schemas.HGLMModelV3.HGLMModelOutputV3

beta - Variable in class hex.schemas.MakeGLMModelV3

beta_constraints - Variable in class hex.schemas.GAMV3.GAMParametersV3

beta_constraints - Variable in class hex.schemas.GLMV3.GLMParametersV3

beta_constraints - Variable in class hex.schemas.ModelSelectionV3.ModelSelectionParametersV3

beta_epsilon - Variable in class hex.schemas.GAMV3.GAMParametersV3

beta_epsilon - Variable in class hex.schemas.GLMV3.GLMParametersV3

beta_epsilon - Variable in class hex.schemas.ModelSelectionV3.ModelSelectionParametersV3

beta_internal() - Method in class hex.glm.GLMModel

beta_std(double) - Method in class hex.glm.GLMModel

BetaConstraint() - Constructor for class hex.glm.GLM.BetaConstraint

BetaConstraint(Frame) - Constructor for class hex.glm.GLM.BetaConstraint

BetaInfo(int, int) - Constructor for class hex.glm.GLM.BetaInfo

betaMultinomial() - Method in class hex.glm.ComputationState

betaMultinomial(int, double[]) - Method in class hex.glm.ComputationState

betaMultinomialFull(int, double[]) - Method in class hex.glm.ComputationState

bin(double) - Method in class hex.tree.DHistogram

bin() - Method in class hex.tree.DTree.Split

binaryEntropy() - Method in class hex.tree.dt.binning.SplitStatistics

binAt(int) - Method in class hex.tree.DHistogram

binIds - Variable in class hex.DataInfo.Row

BinningStrategy - Enum in hex.tree.dt.binning

Strategy for binning.

binomial_double_trees - Variable in class hex.schemas.DRFV3.DRFParametersV3

binomialOpt() - Method in class hex.tree.drf.DRFModel

binomialOpt() - Method in class hex.tree.SharedTreeModel

binomialOpt() - Method in class hex.tree.uplift.UpliftDRFModel

bins(int) - Method in class hex.tree.DHistogram

bits() - Method in class hex.deeplearning.Dropout

blending() - Method in class hex.ensemble.StackedEnsembleModel.StackedEnsembleParameters

blending_frame - Variable in class hex.schemas.StackedEnsembleV99.StackedEnsembleParametersV99

BMulInPlaceTask(DataInfo, double[][], int) - Constructor for class hex.util.LinearAlgebraUtils.BMulInPlaceTask

BMulInPlaceTask(DataInfo, double[][], int, boolean) - Constructor for class hex.util.LinearAlgebraUtils.BMulInPlaceTask

BMulTask(Key<Job>, DataInfo, double[][]) - Constructor for class hex.util.LinearAlgebraUtils.BMulTask

BMulTaskMatrices(Frame) - Constructor for class hex.util.LinearAlgebraUtils.BMulTaskMatrices

bprop(int) - Method in class hex.deeplearning.Neurons

Back propagation of error terms stored in _e (for non-final layers)

bprop(int) - Method in class hex.deeplearning.Neurons.ExpRectifier

bprop(int) - Method in class hex.deeplearning.Neurons.Input

bprop(int) - Method in class hex.deeplearning.Neurons.Maxout

bprop(int) - Method in class hex.deeplearning.Neurons.Output

bprop(int) - Method in class hex.deeplearning.Neurons.Rectifier

bprop(int) - Method in class hex.deeplearning.Neurons.Tanh

bpropMiniBatch(Neurons[], int) - Static method in class hex.deeplearning.DeepLearningTask

Helper to apply back-propagation without clearing out the gradients afterwards Used for gradient checking

bpropOutputLayer(int) - Method in class hex.deeplearning.Neurons

Back-propagate gradient in output layer

BranchInteractionConstraints - Class in hex.tree

Local branch interaction constraints class to save information about allowed interaction between columns indices

BranchInteractionConstraints(IcedHashSet<IcedInt>) - Constructor for class hex.tree.BranchInteractionConstraints

bs - Variable in class hex.schemas.GAMV3.GAMParametersV3

bsv_count - Variable in class hex.schemas.PSVMModelV3.PSVMModelOutputV3

BufStringDecisionPathTracker() - Constructor for class hex.tree.SharedTreeModel.BufStringDecisionPathTracker

build_glm_model - Variable in class hex.schemas.ModelSelectionV3.ModelSelectionParametersV3

build_null_model - Variable in class hex.schemas.GLMV3.GLMParametersV3

build_tree_one_node - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3

buildCalibrationModel(CalibrationHelper.ModelBuilderWithCalibration<M, P, O>, CalibrationHelper.ParamsWithCalibration, Job, M) - Static method in class hex.tree.CalibrationHelper

buildCVGamModels(GAMModel, GLMModel, GAMModel.GAMParameters, String) - Static method in class hex.gam.MatrixFrameUtils.GamUtils

builderVisibility() - Method in class hex.adaboost.AdaBoost

builderVisibility() - Method in class hex.aggregator.Aggregator

builderVisibility() - Method in class hex.coxph.CoxPH

builderVisibility() - Method in class hex.ensemble.StackedEnsemble

builderVisibility() - Method in class hex.gam.GAM

builderVisibility() - Method in class hex.generic.Generic

builderVisibility() - Method in class hex.grep.Grep

builderVisibility() - Method in class hex.hglm.HGLM

builderVisibility() - Method in class hex.isotonic.IsotonicRegression

builderVisibility() - Method in class hex.psvm.PSVM

builderVisibility() - Method in class hex.svd.SVD

builderVisibility() - Method in class hex.tree.dt.DT

builderVisibility() - Method in class hex.tree.isofor.IsolationForest

builderVisibility() - Method in class hex.word2vec.Word2Vec

buildExtractBestR2Model(Frame[], ModelSelectionModel.ModelSelectionParameters, int, String, Model.Parameters.FoldAssignmentScheme) - Static method in class hex.modelselection.ModelSelection

Given the training Frame array, build models for each training frame and return the GLMModel with the best R2 values.

buildGamFrame(GAMModel.GAMParameters, Frame, Key<Frame>[], String) - Static method in class hex.gam.MatrixFrameUtils.GamUtils

buildGLMBuilders(GLMModel.GLMParameters[]) - Static method in class hex.anovaglm.ANOVAGLMUtils

buildGLMBuilders(GLMModel.GLMParameters[]) - Static method in class hex.modelselection.ModelSelectionUtils

buildGLMModel(List<Integer>) - Method in class hex.modelselection.ModelSelection.ModelSelectionDriver

buildGLMParameters(Frame[], ANOVAGLMModel.ANOVAGLMParameters) - Static method in class hex.anovaglm.ANOVAGLMUtils

buildLayer(Frame, int, DTree[], int[], DHistogram[][][], boolean) - Method in class hex.tree.SharedTree

buildLayer(Frame, int, DTree, int[], DHistogram[][][], boolean) - Method in class hex.tree.uplift.UpliftDRF

buildModel() - Method in class hex.deeplearning.DeepLearning.DeepLearningDriver

Train a Deep Learning model, assumes that all members are populated If checkpoint == null, then start training a new model, otherwise continue from a checkpoint

buildModel() - Method in class hex.modelselection.ModelSelection.ModelSelectionDriver

buildNextKTrees() - Method in class hex.tree.SharedTree.Driver

buildNextNode(Queue<DataFeaturesLimits>, int) - Method in class hex.tree.dt.DT

Build next node from the first limits in queue.

buildRIDFrame(GLMModel.GLMParameters, Frame, Frame) - Static method in class hex.glm.GLMUtils

buildSpecificFrame(int[], Frame, String[][], ANOVAGLMModel.ANOVAGLMParameters) - Static method in class hex.anovaglm.ANOVAGLMUtils

This method is used to attach the weight/offset columns if they exist and the response columns, specific transformed columns to a training frames.

buildTable(String[], boolean) - Method in class hex.glrm.GLRM.Archetypes

buildTrainingFrames(Key<Frame>, int, String[][], ANOVAGLMModel.ANOVAGLMParameters) - Static method in class hex.anovaglm.ANOVAGLMUtils

This method will take the frame that contains transformed columns of predictor A, predictor B, interaction of predictor A and B and generate new training frames that contains the following columns: - transformed columns of predictor B, interaction of predictor A and B, response - transformed columns of predictor A, interaction of predictor A and B, response - transformed columns of predictor A, predictor B, response - transformed columns of predictor A, predictor B, interaction of predictor A and B, response The same logic applies if there are more than two individual predictors.

buildTree(double[][], long, int) - Method in class hex.tree.isoforextended.isolationtree.IsolationTree

Implementation of Algorithm 2 (iTree) from paper.

buildVariableInflationFactors(Frame, DataInfo) - Method in class hex.glm.GLMModel

This method will calculate the variable inflation factor of each numerical predictor using the following procedure: 1.

buildVariableInflationFactors(GLMModel.GLMParameters, String[], String[]) - Method in class hex.glm.GLMModel

bulkScore0(Chunk[]) - Method in interface hex.psvm.BulkSupportVectorScorer

BulkScorerFactory - Class in hex.psvm

BulkScorerFactory() - Constructor for class hex.psvm.BulkScorerFactory

BulkSupportVectorScorer - Interface in hex.psvm

C

calc_like - Variable in class hex.schemas.GLMV3.GLMParametersV3

calc_like - Variable in class hex.schemas.ModelSelectionV3.ModelSelectionParametersV3

calcCounts(CoxPHModel, CoxPH.CoxPHTask) - Method in class hex.coxph.CoxPH.CoxPHDriver

calcCumhaz_0(CoxPHModel, CoxPH.CoxPHTask) - Method in class hex.coxph.CoxPH.CoxPHDriver

calcKernel(DataInfo.Row, DataInfo.Row) - Method in interface hex.psvm.psvm.Kernel

calcKernelWithLabel(DataInfo.Row, DataInfo.Row) - Method in interface hex.psvm.psvm.Kernel

calcLoglik(DataInfo, CoxPH.ComputationState, CoxPHModel.CoxPHParameters, CoxPH.CoxPHTask) - Method in class hex.coxph.CoxPH.CoxPHDriver

calcModelStats(CoxPHModel, double[], CoxPH.ComputationState) - Method in class hex.coxph.CoxPH.CoxPHDriver

calculate(int, double, double, double, double) - Method in interface hex.glm.DispersionTask.ComputeMaxSumSeriesTsk.CalWVdWVd2WV

calculate(int, double, double, double, double) - Method in class hex.glm.DispersionTask.ComputeMaxSumSeriesTsk.EvalLogD2WVEnv

calculate(int, double, double, double, double) - Method in class hex.glm.DispersionTask.ComputeMaxSumSeriesTsk.EvalLogDWVEnv

calculate(int, double, double, double, double) - Method in class hex.glm.DispersionTask.ComputeMaxSumSeriesTsk.EvalLogWVEnv

calculateConstraintSquare(ComputationState, ConstrainedGLMUtils.LinearConstraints[], ConstrainedGLMUtils.LinearConstraints[]) - Static method in class hex.glm.ConstrainedGLMUtils

calculatem(int) - Static method in class hex.gam.GamSplines.ThinPlateRegressionUtils

For thin plate regression, given d (number of predictors for a smooth), it will return m where (m-1) is the maximum polynomial degree in the polynomial basis functions.

calculateM(int, int) - Static method in class hex.gam.GamSplines.ThinPlateRegressionUtils

calculatePredComboNumber(int, int) - Static method in class hex.anovaglm.ANOVAGLMUtils

Given the number of individual predictors, the highest order of interaction terms allowed, this method will calculate the total number of predictors that will be used to build the full model.

calculatePValuesFromZValues(double[], boolean, long) - Static method in class hex.glm.GLMModel.GLMOutput

calculateSplitStatisticsForCategoricalFeature() - Method in class hex.tree.dt.binning.FeatureBins

calculateSplitStatisticsForCategoricalFeature(int) - Method in class hex.tree.dt.binning.Histogram

calculateSplitStatisticsForNumericFeature() - Method in class hex.tree.dt.binning.FeatureBins

Calculates statistics for bins depending on all other bins - see BinAccumulatedStatistics.

calculateSplitStatisticsForNumericFeature(int) - Method in class hex.tree.dt.binning.Histogram

calculateStatisticsForCategoricalFeatureBinomialClassification() - Method in class hex.tree.dt.binning.FeatureBins

calculateStdErrFromZValues(double[], double[]) - Static method in class hex.glm.GLMModel.GLMOutput

calculateVarimp() - Method in class hex.glm.GLMModel.GLMOutput

calculateVarimpBase(double[], int[], double[]) - Static method in class hex.schemas.GLMModelV3

calculateVarimpMultinomial(double[], int[], double[][]) - Static method in class hex.schemas.GLMModelV3.GLMModelOutputV3

calDerivatives(ConstrainedGLMUtils.LinearConstraints[], List<String>) - Static method in class hex.glm.ComputationState

This methold will calculate the first derivative of h(beta).

calDerivConst(Chunk[], NewChunk[], int, int[]) - Method in class hex.glm.DispersionTask.ComputeTweedieConstTsk

calGradient(double[], ComputationState, GLM.GLMGradientSolver, double[], double[], ConstrainedGLMUtils.LinearConstraints[], ConstrainedGLMUtils.LinearConstraints[]) - Static method in class hex.glm.ConstrainedGLMUtils

This method calls getGradient to calculate the gradient, likelhood and objective function values.

calGram(ConstrainedGLMUtils.ConstraintsDerivatives[]) - Static method in class hex.glm.ComputationState

This method to calculate contribution of penalty to gram (d2H/dbidbj), refer to the doc Section VI.II

calHGLMLlg(long, double[][], double, double[][][], double, double[][]) - Static method in class hex.hglm.MetricBuilderHGLM

This method calculates the log-likelihood as described in section II.V of the doc.

calibrate_model - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3

calibrateModel() - Method in interface hex.tree.CalibrationHelper.ParamsWithCalibration

calibrateModel() - Method in class hex.tree.SharedTreeModel.SharedTreeParameters

calibration_frame - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3

calibration_method - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3

CalibrationHelper - Class in hex.tree

CalibrationHelper() - Constructor for class hex.tree.CalibrationHelper

CalibrationHelper.CalibrationMethod - Enum in hex.tree

CalibrationHelper.ModelBuilderWithCalibration<M extends hex.Model<M,P,O>,P extends hex.Model.Parameters,O extends hex.Model.Output> - Interface in hex.tree

CalibrationHelper.OutputWithCalibration - Interface in hex.tree

CalibrationHelper.ParamsWithCalibration - Interface in hex.tree

calibrationModel() - Method in interface hex.tree.CalibrationHelper.OutputWithCalibration

calibrationModel() - Method in class hex.tree.SharedTreeModel.SharedTreeOutput

calInvTPZjTZ(double[][], double[][], double) - Static method in class hex.hglm.MetricBuilderHGLM

calJMaxConst(Chunk[], NewChunk[], int, int) - Method in class hex.glm.DispersionTask.ComputeTweedieConstTsk

calLogWVMax(Chunk[], int, int, double) - Method in class hex.glm.DispersionTask.ComputeMaxSumSeriesTsk

calLogZ(Chunk[], int, int) - Method in class hex.glm.DispersionTask.ComputeMaxSumSeriesTsk

calMultipliersNGradients(double[][], double[][], double[], double[], int[], Chunk, Chunk[], int, int, int) - Method in class hex.glm.GLMTask.GLMMultinomialGradientBaseTask

calMultipliersNGradients(double[][], double[][], double[], double[], int[], Chunk, Chunk[], int, int, int) - Method in class hex.glm.GLMTask.GLMMultinomialGradientTask

calPart1LogConst(Chunk[], NewChunk[], int, int) - Method in class hex.glm.DispersionTask.ComputeTweedieConstTsk

calPart1LogPIConst(Chunk[], NewChunk[], int, int) - Method in class hex.glm.DispersionTask.ComputeTweedieConstTsk

calPart2Const(Chunk[], NewChunk[], int, int) - Method in class hex.glm.DispersionTask.ComputeTweedieConstTsk

calR2Scale(Frame, String) - Static method in class hex.modelselection.ModelSelectionUtils

calSmoothNess(double[], double[][][], int[][]) - Static method in class hex.glm.GLMUtils

calSmoothNess(double[][], double[][][], int[][]) - Static method in class hex.glm.GLMUtils

calTauEvarEq17(double, double, double[][][], double[][][], double) - Static method in class hex.hglm.HGLMUtils

calZConst(Chunk[], NewChunk[], int, int) - Method in class hex.glm.DispersionTask.ComputeTweedieConstTsk

can_build() - Method in class hex.adaboost.AdaBoost

can_build() - Method in class hex.aggregator.Aggregator

can_build() - Method in class hex.anovaglm.ANOVAGLM

can_build() - Method in class hex.coxph.CoxPH

can_build() - Method in class hex.deeplearning.DeepLearning

Types of models we can build with DeepLearning

can_build() - Method in class hex.ensemble.StackedEnsemble

can_build() - Method in class hex.gam.GAM

can_build() - Method in class hex.generic.Generic

can_build() - Method in class hex.glm.GLM

can_build() - Method in class hex.glrm.GLRM

can_build() - Method in class hex.grep.Grep

can_build() - Method in class hex.hglm.HGLM

can_build() - Method in class hex.isotonic.IsotonicRegression

can_build() - Method in class hex.kmeans.KMeans

can_build() - Method in class hex.modelselection.ModelSelection

can_build() - Method in class hex.naivebayes.NaiveBayes

can_build() - Method in class hex.pca.PCA

can_build() - Method in class hex.psvm.PSVM

can_build() - Method in class hex.rulefit.RuleFit

can_build() - Method in class hex.svd.SVD

can_build() - Method in class hex.tree.drf.DRF

can_build() - Method in class hex.tree.dt.DT

can_build() - Method in class hex.tree.gbm.GBM

can_build() - Method in class hex.tree.isofor.IsolationForest

can_build() - Method in class hex.tree.isoforextended.ExtendedIsolationForest

can_build() - Method in class hex.tree.uplift.UpliftDRF

can_build() - Method in class hex.word2vec.Word2Vec

canLearnFromNAs() - Method in class hex.tree.SharedTree

canonical() - Method in class hex.glm.GLMModel.GLMParameters

catcnt - Variable in class water.api.ModelMetricsGLRMV99

CategoricalBin - Class in hex.tree.dt.binning

For categorical features values are already binned to categories - each bin corresponds to one value (category)

CategoricalBin(int, int, int) - Constructor for class hex.tree.dt.binning.CategoricalBin

CategoricalBin(int) - Constructor for class hex.tree.dt.binning.CategoricalBin

CategoricalFeatureLimits - Class in hex.tree.dt

Limits for one feature.

CategoricalFeatureLimits(boolean[]) - Constructor for class hex.tree.dt.CategoricalFeatureLimits

CategoricalFeatureLimits(double[]) - Constructor for class hex.tree.dt.CategoricalFeatureLimits

CategoricalFeatureLimits(int) - Constructor for class hex.tree.dt.CategoricalFeatureLimits

CategoricalSplittingRule - Class in hex.tree.dt

CategoricalSplittingRule(int, boolean[], double) - Constructor for class hex.tree.dt.CategoricalSplittingRule

CategoricalSplittingRule(boolean[]) - Constructor for class hex.tree.dt.CategoricalSplittingRule

caterr - Variable in class water.api.ModelMetricsGLRMV99

catNAFill() - Method in class hex.DataInfo

catNAFill(int) - Method in class hex.DataInfo

catTreshold - Variable in class hex.rulefit.Condition

centers - Variable in class hex.schemas.KMeansModelV3.KMeansModelOutputV3

centers_std - Variable in class hex.schemas.KMeansModelV3.KMeansModelOutputV3

centralizeFrame(Frame, String, GAMModel.GAMParameters) - Method in class hex.gam.MatrixFrameUtils.GenCSSplineGamOneColumn

centralizeFrame(Frame, String, GAMModel.GAMParameters, double[][]) - Static method in class hex.gam.MatrixFrameUtils.GenCSSplineGamOneColumn

centralizeFrame(Frame, String, GAMModel.GAMParameters) - Method in class hex.gam.MatrixFrameUtils.GenMSplineGamOneColumn

changeCoeffBetainfo(String[]) - Method in class hex.glm.GLM.GLMDriver

check() - Method in class hex.glm.GLM.BetaConstraint

check_constant_response - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3

checkConsistency() - Method in class hex.aggregator.AggregatorModel

checkDistributions() - Method in class hex.psvm.PSVM

checkEarlyStoppingReproducibility() - Method in class hex.tree.SharedTree

checkFrameRowNA(Frame, long) - Static method in class hex.gam.GamSplines.ThinPlateRegressionUtils

checkGAMParamsLengths() - Method in class hex.gam.GAM

Check and make sure if related parameters are defined, they must be of correct length.

checkInteractionConstraints(ModelBuilder<?, ?, ?>, Frame, String[][]) - Static method in class hex.tree.TreeUtils

checkKKTConditions(double[], GLM.GLMGradientInfo, int) - Method in class hex.glm.GLM.GLMDriver

We will check it the constraint stopping conditions are met.

checkKKTs() - Method in class hex.glm.ComputationState

checkKKTsMultinomial() - Method in class hex.glm.ComputationState

checkMemoryFootPrint(DataInfo) - Method in class hex.glm.GLM

checkMemoryFootPrint(int) - Method in class hex.modelselection.ModelSelection

checkMemoryFootPrint_impl() - Method in class hex.deeplearning.DeepLearning

checkMemoryFootPrint_impl() - Method in class hex.glrm.GLRM

checkMemoryFootPrint_impl() - Method in class hex.kmeans.KMeans

checkMemoryFootPrint_impl() - Method in class hex.naivebayes.NaiveBayes

checkMemoryFootPrint_impl() - Method in class hex.pca.PCA

checkMemoryFootPrint_impl() - Method in class hex.svd.SVD

checkMemoryFootPrint_impl() - Method in class hex.tree.isoforextended.ExtendedIsolationForest

checkMemoryFootPrint_impl() - Method in class hex.tree.SharedTree

checkMonotoneConstraints(ModelBuilder<?, ?, ?>, Frame, KeyValue[]) - Static method in class hex.tree.TreeUtils

checkNFamilyNLinkAssignment() - Method in class hex.gam.GAM

check if _parms._family = AUTO, the correct link functions are assigned according to the response type.

checkNonAutoParmsNotChanged(Model.Parameters, Model.Parameters) - Method in class hex.deeplearning.DeepLearning.DeepLearningDriver

checkOrChooseNumKnots() - Method in class hex.gam.GAM

set default num_knots to 10 for gam_columns where there is no knot_id specified for CS smoothers for TP smoothers, default is set to be max of 10 or _M+2.

CheckpointUtils - Class in hex.util

CheckpointUtils() - Constructor for class hex.util.CheckpointUtils

checkPositiveG(int, double[][]) - Static method in class hex.hglm.HGLMUtils

checkRowNA(Chunk[], int) - Static method in class hex.gam.GamSplines.ThinPlateRegressionUtils

checksum_impl() - Method in class hex.DataInfo

checksum_impl() - Method in class hex.deeplearning.DeepLearningModel

checksum_impl() - Method in class hex.deeplearning.DeepLearningModelInfo

Unique identifier for this model's state, based on raw numbers

checksum_impl() - Method in class hex.glm.GLMModel

checksum_impl() - Method in class hex.glm.GLMModel.GLMOutput

checksum_impl() - Method in class hex.tree.CompressedTree

checkThinPlateParams() - Method in class hex.gam.GAM

verify and check thin plate regression smoothers specific parameters

checkTrainRowNumKnots() - Method in class hex.gam.GAM

Check and make sure the there are enough number of rows in the training dataset to accomodate the num_knot settings.

ChiSquaredDivergence - Class in hex.tree.uplift

ChiSquaredDivergence() - Constructor for class hex.tree.uplift.ChiSquaredDivergence

chk_nids(Chunk[], int) - Method in class hex.tree.SharedTree

chk_offset(Chunk[]) - Method in class hex.tree.SharedTree

chk_oobt(Chunk[]) - Method in class hex.tree.SharedTree

chk_resp(Chunk[]) - Method in class hex.tree.SharedTree

chk_tree(Chunk[], int) - Method in class hex.tree.SharedTree

chk_weight(Chunk[]) - Method in class hex.tree.SharedTree

chk_work(Chunk[], int) - Method in class hex.tree.SharedTree

chol2Inv(double[][], boolean) - Static method in class hex.util.LinearAlgebraUtils

chol2Inv(double[][]) - Static method in class hex.util.LinearAlgebraUtils

Given the cholesky decomposition of X = QR, this method will return the inverse of transpose(X)*X by attempting to solve for transpose(R)*R*XTX_inverse = Identity matrix

cholesky(Gram.Cholesky, double[][]) - Method in class hex.glm.ComputationState.GramGrad

cholesky(Gram.Cholesky) - Method in class hex.gram.Gram

cholesky(Gram.Cholesky, boolean, String) - Method in class hex.gram.Gram

Compute the Cholesky decomposition.

Cholesky(double[][], double[]) - Constructor for class hex.gram.Gram.Cholesky

Cholesky(double[][], double[], boolean) - Constructor for class hex.gram.Gram.Cholesky

choleskySymDiagMat(double[][]) - Static method in class hex.util.LinearAlgebraUtils

compute the cholesky of xx which stores the lower part of a symmetric square tridiagonal matrix.

chunkDone(long) - Method in class hex.deeplearning.DeepLearningTask

After each chunk, add the number of processed rows to the counter

chunkDone(long) - Method in class hex.FrameTask

Override this to do post-chunk processing work.

chunkDone() - Method in class hex.FrameTask2

Perform action after processing one "chunk" of data/

chunkDone() - Method in class hex.glm.GLMTask.GLMIterationTask

chunkDone() - Method in class hex.gram.Gram.GramTask

chunkDone() - Method in class hex.gram.Gram.OuterGramTask

chunkInit() - Method in class hex.coxph.CoxPH.CoxPHTask

chunkInit() - Method in class hex.deeplearning.DeepLearningTask

chunkInit() - Method in class hex.FrameTask

Override this to initialize at the beginning of chunk processing.

chunkInit() - Method in class hex.FrameTask2

Initialization method, called once per "chunk".

chunkInit() - Method in class hex.glm.GLMTask.ComputeDiTriGammaTsk

chunkInit() - Method in class hex.glm.GLMTask.ComputeGammaMLSETsk

chunkInit() - Method in class hex.glm.GLMTask.ComputeSEorDEVIANCETsk

chunkInit() - Method in class hex.glm.GLMTask.GLMIterationTask

chunkInit() - Method in class hex.glm.GLMTask.GLMIterationTaskMultinomial

chunkInit() - Method in class hex.glm.GLMTask.GLMMultinomialUpdate

chunkInit() - Method in class hex.glm.GLMTask.GLMMultinomialWLSTask

chunkInit() - Method in class hex.glm.GLMTask.GLMWLSTask

chunkInit() - Method in class hex.glm.GLMTask.LSTask

chunkInit() - Method in class hex.gram.Gram.GramTask

chunkInit() - Method in class hex.gram.Gram.OuterGramTask

cid - Variable in class hex.DataInfo.Row

class_sampling_factors - Variable in class hex.schemas.ANOVAGLMV3.ANOVAGLMParametersV3

Desired over/under-sampling ratios per class (lexicographic order).

class_sampling_factors - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

Desired over/under-sampling ratios per class (lexicographic order).

class_sampling_factors - Variable in class hex.schemas.GAMV3.GAMParametersV3

Desired over/under-sampling ratios per class (lexicographic order).

class_sampling_factors - Variable in class hex.schemas.GLMV3.GLMParametersV3

Desired over/under-sampling ratios per class (lexicographic order).

class_sampling_factors - Variable in class hex.schemas.ModelSelectionV3.ModelSelectionParametersV3

Desired over/under-sampling ratios per class (lexicographic order).

class_sampling_factors - Variable in class hex.schemas.NaiveBayesV3.NaiveBayesParametersV3

Desired over/under-sampling ratios per class (lexicographic order).

class_sampling_factors - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3

Desired over/under-sampling ratios per class (lexicographic order).

classification_stop - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

The stopping criteria in terms of classification error (1-accuracy) on the training data scoring dataset.

classNames() - Method in class hex.gam.GAMModel.GAMModelOutput

Names of levels for a categorical response column.

classNames() - Method in class hex.glm.GLMModel.GLMOutput

classNames() - Method in class hex.isotonic.IsotonicRegressionModel.IsotonicRegressionOutput

classNames() - Method in class hex.tree.gbm.GBMModel.GBMOutput

classPrediction - Variable in class hex.tree.dt.DTPrediction

cleanup() - Method in class hex.ensemble.Metalearner

cleanUp() - Method in class hex.glm.TweedieMLDispersionOnly

cleanUpInputFrame(Frame) - Method in class hex.gam.GAMModel

cleanUpInputFrame(Frame, GAMModel.GAMParameters, String[][], double[][][], double[][][], double[][][], double[][][], int[][][], double[][], double[][], int[]) - Static method in class hex.gam.GAMModel

clone() - Method in class hex.tree.dt.AbstractFeatureLimits

clone() - Method in class hex.tree.dt.binning.AbstractBin

clone() - Method in class hex.tree.dt.binning.CategoricalBin

clone() - Method in class hex.tree.dt.binning.NumericBin

clone() - Method in class hex.tree.dt.CategoricalFeatureLimits

clone() - Method in class hex.tree.dt.DataFeaturesLimits

clone() - Method in class hex.tree.dt.NumericFeatureLimits

closeLocal() - Method in class hex.deeplearning.DeepLearningTask

After all maps are done on a node, this is called to store the per-node model into DKV (for elastic averaging) Otherwise, do nothing.

closeLocal() - Method in class hex.FrameTask

cluster_size_constraints - Variable in class hex.schemas.KMeansV3.KMeansParametersV3

ClusteringUtils - Class in hex.util

ClusteringUtils() - Constructor for class hex.util.ClusteringUtils

COD_solve(ComputationState.GramXY, double, double) - Method in class hex.glm.GLM

coefficient_names - Variable in class hex.schemas.GLMRegularizationPathV3

coefficient_names - Variable in class hex.schemas.HGLMModelV3.HGLMModelOutputV3

coefficientNames() - Method in class hex.anovaglm.ANOVAGLMModel.ANOVAGLMModelOutput

coefficientNames() - Method in class hex.glm.GLMModel.GLMOutput

coefficientNames() - Method in class hex.modelselection.ModelSelectionModel.ModelSelectionModelOutput

coefficients() - Method in class hex.glm.GLMModel

get beta coefficients in a map indexed by name

coefficients(boolean) - Method in class hex.glm.GLMModel

coefficients() - Method in class hex.modelselection.ModelSelectionModel

coefficients(boolean) - Method in class hex.modelselection.ModelSelectionModel

coefficients(int) - Method in class hex.modelselection.ModelSelectionModel

coefficients(int, boolean) - Method in class hex.modelselection.ModelSelectionModel

coefficients - Variable in class hex.schemas.GLMRegularizationPathV3

coefficients_std - Variable in class hex.schemas.GLMRegularizationPathV3

CoefIndices - Interface in hex.glm

CoefIndices(int, int) - Constructor for class hex.glm.ConstrainedGLMUtils.CoefIndices

coefNames() - Method in class hex.DataInfo

coefOriginalColumnIndices(Frame) - Method in class hex.DataInfo

coefOriginalColumnIndices() - Method in class hex.DataInfo

coefOriginalNames(Frame) - Method in class hex.DataInfo

coefOriginalNames() - Method in class hex.DataInfo

coefs - Variable in class hex.optimization.L_BFGS.Result

col() - Method in class hex.tree.DTree.Split

col_major - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

col_sample_rate - Variable in class hex.schemas.GBMV3.GBMParametersV3

col_sample_rate_change_per_level - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3

col_sample_rate_per_tree - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3

cold_start - Variable in class hex.schemas.GAMV3.GAMParametersV3

cold_start - Variable in class hex.schemas.GLMV3.GLMParametersV3

cold_start - Variable in class hex.schemas.ModelSelectionV3.ModelSelectionParametersV3

CollinearColumnsException() - Constructor for exception hex.gram.Gram.CollinearColumnsException

CollinearColumnsException(String) - Constructor for exception hex.gram.Gram.CollinearColumnsException

collinearInConstraints(String[], String[]) - Static method in class hex.glm.ConstrainedGLMUtils

cols() - Method in class hex.coxph.Storage.DenseRowMatrix

cols() - Method in interface hex.coxph.Storage.Matrix

cols() - Method in class hex.deeplearning.Storage.DenseColMatrix

cols() - Method in class hex.deeplearning.Storage.DenseRowMatrix

cols() - Method in interface hex.deeplearning.Storage.Matrix

cols() - Method in class hex.deeplearning.Storage.SparseRowMatrix

cols() - Method in interface hex.deeplearning.Storage.Tensor

combineAndFlat(String[][]) - Static method in class hex.anovaglm.ANOVAGLMUtils

combineConstraints(ConstrainedGLMUtils.LinearConstraints[], ConstrainedGLMUtils.LinearConstraints[]) - Static method in class hex.glm.ConstrainedGLMUtils

combineScoringHistory(TwoDimTable, TwoDimTable) - Static method in class hex.glm.GLMUtils

combineTableContents(TwoDimTable, TwoDimTable, TwoDimTable, List<Integer>, int, int, int) - Static method in class hex.glm.GLMUtils

compareTo(EigenPair) - Method in class hex.util.EigenPair

Compare an eigenPair = (eigenvalue, eigenVector) against otherEigenPair based on respective eigenValues

compress(int, int, String[][]) - Method in class hex.tree.DTree

compress(AutoBuffer, AutoBuffer) - Method in class hex.tree.DTree.DecidedNode

compress(AutoBuffer, AutoBuffer) - Method in class hex.tree.DTree.LeafNode

compress(AutoBuffer, AutoBuffer) - Method in class hex.tree.DTree.Node

compress(AutoBuffer, AutoBuffer) - Method in class hex.tree.DTree.UndecidedNode

CompressedDT - Class in hex.tree.dt

Compressed DT class containing tree as array.

CompressedDT(AbstractCompressedNode[], int) - Constructor for class hex.tree.dt.CompressedDT

CompressedForest - Class in hex.tree

Collection of Compressed Trees contains: - keys to trees - metadata shared among all the trees (eg.

CompressedForest(Key<CompressedTree>[][], String[][]) - Constructor for class hex.tree.CompressedForest

CompressedForest.LocalCompressedForest - Class in hex.tree

Node-local representation of a collection of trees.

CompressedIsolationTree - Class in hex.tree.isoforextended.isolationtree

IsolationTree structure with better memory performance.

CompressedIsolationTree(int) - Constructor for class hex.tree.isoforextended.isolationtree.CompressedIsolationTree

CompressedLeaf - Class in hex.tree.dt

CompressedLeaf(double, double) - Constructor for class hex.tree.dt.CompressedLeaf

CompressedLeaf - Class in hex.tree.isoforextended.isolationtree

IsolationTree Leaf Node with better memory performance.

CompressedLeaf(IsolationTree.Node) - Constructor for class hex.tree.isoforextended.isolationtree.CompressedLeaf

CompressedLeaf(int, int) - Constructor for class hex.tree.isoforextended.isolationtree.CompressedLeaf

CompressedNode - Class in hex.tree.dt

CompressedNode(AbstractSplittingRule) - Constructor for class hex.tree.dt.CompressedNode

CompressedNode - Class in hex.tree.isoforextended.isolationtree

IsolationTree Node with better memory performance.

CompressedNode(IsolationTree.Node) - Constructor for class hex.tree.isoforextended.isolationtree.CompressedNode

CompressedNode(double[], double[], int) - Constructor for class hex.tree.isoforextended.isolationtree.CompressedNode

CompressedTree - Class in hex.tree

CompressedTree(byte[], long, int, int) - Constructor for class hex.tree.CompressedTree

ComputationEngineTask(Job, HGLMModel.HGLMParameters, DataInfo) - Constructor for class hex.hglm.HGLMTask.ComputationEngineTask

ComputationState - Class in hex.glm

ComputationState(Job, GLMModel.GLMParameters, DataInfo, GLM.BetaConstraint, GLM.BetaInfo) - Constructor for class hex.glm.ComputationState

ComputationState(Job, GLMModel.GLMParameters, DataInfo, GLM.BetaConstraint, GLM.BetaInfo, double[][][], int[][]) - Constructor for class hex.glm.ComputationState

ComputationState.GLMSubsetGinfo - Class in hex.glm

This method will grab a subset of the gradient for each multinomial class.

ComputationState.GramGrad - Class in hex.glm

ComputationState.GramXY - Class in hex.glm

Cached state of COD (with covariate updates) solver.

ComputationStateHGLM - Class in hex.hglm

ComputationStateHGLM(Job, HGLMModel.HGLMParameters, DataInfo, HGLMTask.ComputationEngineTask, int) - Constructor for class hex.hglm.ComputationStateHGLM

ComputationStateHGLM.ComputationStateSimple - Class in hex.hglm

ComputationStateSimple(double[], double[][], double[][], double) - Constructor for class hex.hglm.ComputationStateHGLM.ComputationStateSimple

compute(Vec, Vec, Vec) - Method in class hex.glm.TweedieEstimator

compute() - Method in class hex.tree.DTree.DecidedNode.FindSplits

compute2() - Method in class hex.tree.SharedTree.ScoreBuildOneTree

compute_metrics - Variable in class hex.schemas.NaiveBayesV3.NaiveBayesParametersV3

compute_metrics - Variable in class hex.schemas.PCAV3.PCAParametersV3

compute_p_values - Variable in class hex.schemas.ANOVAGLMV3.ANOVAGLMParametersV3

compute_p_values - Variable in class hex.schemas.GAMV3.GAMParametersV3

compute_p_values - Variable in class hex.schemas.GLMV3.GLMParametersV3

compute_p_values - Variable in class hex.schemas.ModelSelectionV3.ModelSelectionParametersV3

computeAIC() - Method in class hex.gam.MetricBuilderGAM

computeAIC(GLMModel) - Method in class hex.glm.GLMMetricBuilder

computeCategoricalEtas(Chunk[], double[][], double[], int[]) - Method in class hex.glm.GLMTask.GLMMultinomialGradientBaseTask

computeCategoricalGrads(Chunk[], double[][], double[], int[]) - Method in class hex.glm.GLMTask.GLMMultinomialGradientBaseTask

computeCrossValidation() - Method in class hex.glm.GLM

GLM implementation of N-fold cross-validation.

ComputeDiTriGammaTsk(H2O.H2OCountedCompleter, DataInfo, Key, double[], GLMModel.GLMParameters, double) - Constructor for class hex.glm.GLMTask.ComputeDiTriGammaTsk

ComputeGammaMLSETsk(H2O.H2OCountedCompleter, DataInfo, Key, double[], GLMModel.GLMParameters) - Constructor for class hex.glm.GLMTask.ComputeGammaMLSETsk

computeGradientMultipliers(double[], double[], double[]) - Method in class hex.glm.GLMTask.GLMGaussianGradientTask

computeGram(int, GramV3) - Method in class hex.api.MakeGLMModelHandler

computeGram(double[], GLM.GLMGradientInfo) - Method in class hex.glm.ComputationState

This function calculates the following values: 1.

computeGram(double[], GLMModel.GLMParameters.Solver) - Method in class hex.glm.ComputationState

computeGramRCC(double[], GLMModel.GLMParameters.Solver) - Method in class hex.glm.ComputationState

This method is used only for multinomial family.

computeImpl() - Method in class hex.coxph.CoxPH.CoxPHDriver

computeImpl() - Method in class hex.deeplearning.DeepLearning.DeepLearningDriver

computeImpl() - Method in class hex.glm.GLM.GLMDriver

computeImpl() - Method in class hex.modelselection.ModelSelection.ModelSelectionDriver

computeImpl() - Method in class hex.tree.SharedTree.Driver

ComputeMaxSumSeriesTsk(TweedieMLDispersionOnly, GLMModel.GLMParameters, boolean) - Constructor for class hex.glm.DispersionTask.ComputeMaxSumSeriesTsk

ComputeNewBetaVarEstimatedGaussian(double[][], double[], Job, DataInfo, double[][], double, double, double[]) - Constructor for class hex.glm.RegressionInfluenceDiagnosticsTasks.ComputeNewBetaVarEstimatedGaussian

computeNewGram(DataInfo, double[], GLMModel.GLMParameters.Solver) - Method in class hex.glm.ComputationState

computeNumericEtas(Chunk[], double[][], double[], int[]) - Method in class hex.glm.GLMTask.GLMMultinomialGradientBaseTask

computeNumericGrads(Chunk[], double[][], double[], int[]) - Method in class hex.glm.GLMTask.GLMMultinomialGradientBaseTask

computePathLength(double[]) - Method in class hex.tree.isoforextended.isolationtree.CompressedIsolationTree

Implementation of Algorithm 3 (pathLength) from paper.

computePriorClassDistribution() - Method in class hex.gam.GAM

computePriorClassDistribution() - Method in class hex.glm.GLM

computePriorClassDistribution() - Method in class hex.psvm.PSVM

computePriorClassDistribution() - Method in class hex.tree.SharedTree

computeQ(Key<Job>, DataInfo, Frame, double[][]) - Static method in class hex.util.LinearAlgebraUtils

Solve for Q from Y = QR factorization and write into new frame

computeQ(Key<Job>, DataInfo, Frame) - Static method in class hex.util.LinearAlgebraUtils

computeQInPlace(Key<Job>, DataInfo) - Static method in class hex.util.LinearAlgebraUtils

Solve for Q from Y = QR factorization and write into Y frame

computeR(Key<Job>, DataInfo, boolean) - Static method in class hex.util.LinearAlgebraUtils

Get R = L' from Cholesky decomposition Y'Y = LL' (same as R from Y = QR)

ComputeSEorDEVIANCETsk(H2O.H2OCountedCompleter, DataInfo, Key, double[], GLMModel.GLMParameters, GLMModel) - Constructor for class hex.glm.GLMTask.ComputeSEorDEVIANCETsk

computeSplit() - Method in class hex.tree.DTree.DecidedNode.FindSplits

computeStats() - Method in class hex.deeplearning.DeepLearningModelInfo

Compute statistics about this model on all nodes

computeSubmodel(int, double, double, double) - Method in class hex.glm.GLM.GLMDriver

ComputeTweedieConstTsk(double, Frame) - Constructor for class hex.glm.DispersionTask.ComputeTweedieConstTsk

computeVariableImportances() - Method in class hex.deeplearning.DeepLearningModelInfo

Compute Variable Importance, based on GEDEON: DATA MINING OF INPUTS: ANALYSING MAGNITUDE AND FUNCTIONAL MEASURES

computeWeights(double, double, double, double, GLMModel.GLMWeights) - Method in class hex.glm.GLMModel.GLMWeightsFun

concateGamVecs(Key<Frame>[]) - Static method in class hex.gam.MatrixFrameUtils.GamUtils

Condition - Class in hex.rulefit

Condition(int, Condition.Type, Condition.Operator, double, String[], int[], String, boolean) - Constructor for class hex.rulefit.Condition

Condition.Operator - Enum in hex.rulefit

Condition.Type - Enum in hex.rulefit

ConstrainedGLMUtils - Class in hex.glm

ConstrainedGLMUtils() - Constructor for class hex.glm.ConstrainedGLMUtils

ConstrainedGLMUtils.CoefIndices - Class in hex.glm

ConstrainedGLMUtils.ConstraintGLMStates - Class in hex.glm

ConstrainedGLMUtils.ConstraintsDerivatives - Class in hex.glm

ConstrainedGLMUtils.ConstraintsGram - Class in hex.glm

ConstrainedGLMUtils.LinearConstraintConditions - Class in hex.glm

ConstrainedGLMUtils.LinearConstraints - Class in hex.glm

constraint2Str(ConstrainedGLMUtils.LinearConstraints, String, ComputationState) - Static method in class hex.glm.ConstrainedGLMUtils

constraint_alpha - Variable in class hex.schemas.GLMV3.GLMParametersV3

constraint_beta - Variable in class hex.schemas.GLMV3.GLMParametersV3

constraint_c0 - Variable in class hex.schemas.GLMV3.GLMParametersV3

constraint_eta0 - Variable in class hex.schemas.GLMV3.GLMParametersV3

constraint_tau - Variable in class hex.schemas.GLMV3.GLMParametersV3

ConstraintGLMStates(String[], double[][], GLMModel.GLMParameters) - Constructor for class hex.glm.ConstrainedGLMUtils.ConstraintGLMStates

Constraints - Class in hex.tree

Constraints(int[], Distribution, boolean) - Constructor for class hex.tree.Constraints

constraints(Frame) - Method in class hex.tree.gbm.GBMModel.GBMParameters

ConstraintsDerivatives(boolean) - Constructor for class hex.glm.ConstrainedGLMUtils.ConstraintsDerivatives

ConstraintsGram() - Constructor for class hex.glm.ConstrainedGLMUtils.ConstraintsGram

constraintsStop(GLM.GLMGradientInfo, ComputationState) - Static method in class hex.glm.ConstrainedGLMUtils

This method will check if the stopping conditions for constraint GLM are met and they are namely: 1.

constructGram(ConstrainedGLMUtils.ConstraintsDerivatives) - Static method in class hex.glm.ComputationState

This method is not called often.

contamination - Variable in class hex.schemas.IsolationForestV3.IsolationForestParametersV3

ContributionsMeanAggregator - Class in hex

ContributionsMeanAggregator(Job, int, int, int) - Constructor for class hex.ContributionsMeanAggregator

ContributionsWithBackgroundFrameTask<T extends ContributionsWithBackgroundFrameTask<T>> - Class in hex

Calls map(Chunk[] frame, Chunk[] background, NewChunk[] ncs) by copying the smaller frame across the nodes.

ContributionsWithBackgroundFrameTask(Key<Frame>, Key<Frame>, boolean) - Constructor for class hex.ContributionsWithBackgroundFrameTask

converged() - Method in class hex.glm.ComputationState

converged - Variable in class hex.optimization.L_BFGS.Result

convertCenterBeta2Beta(double[][][], int, double[], int, String[][], boolean) - Static method in class hex.gam.MatrixFrameUtils.GAMModelUtils

convertList2Array(List<Integer[]>, int, int) - Static method in class hex.gam.GamSplines.ThinPlateRegressionUtils

convertParameters(ModelParameter[]) - Static method in class hex.generic.GenericModelParameters

copy3DArray(double[][][]) - Static method in class hex.hglm.HGLMUtils

copyCVGLMtoGAMModel(GAMModel, GLMModel, GAMModel.GAMParameters, String) - Static method in class hex.gam.MatrixFrameUtils.GamUtils

copyGInfo(GLM.GLMGradientInfo) - Static method in class hex.glm.GLMUtils

copyGLMCoeffNames2GAMCoeffNames(GAMModel, GLMModel) - Static method in class hex.gam.MatrixFrameUtils.GAMModelUtils

copyGLMCoeffs(GLMModel, GAMModel, GAMModel.GAMParameters, int) - Static method in class hex.gam.MatrixFrameUtils.GAMModelUtils

copyGLMCoeffs2GAMCoeffs(GAMModel, GLMModel, GLMModel.GLMParameters.Family, int, int, boolean) - Static method in class hex.gam.MatrixFrameUtils.GAMModelUtils

copyGLMtoGAMModel(GAMModel, GLMModel, GAMModel.GAMParameters, boolean) - Static method in class hex.gam.MatrixFrameUtils.GAMModelUtils

copyKnots(double[][][], String[][]) - Method in class hex.gam.GAMModel.GAMModelOutput

The function will copy over the knot locations into _knot_locations and the gam column names corresponding to the knot locations into _gam_knot_column_names.

copyLeftValues(SplitStatistics) - Method in class hex.tree.dt.binning.SplitStatistics

copyMetrics(GAMModel, Frame, boolean, ModelMetrics) - Method in class hex.gam.GAMModel.GAMModelOutput

CopyQtoQMatrix() - Constructor for class hex.util.LinearAlgebraUtils.CopyQtoQMatrix

copyRightValues(SplitStatistics) - Method in class hex.tree.dt.binning.SplitStatistics

copyTwoDimTable(TwoDimTable, String) - Static method in class hex.gam.MatrixFrameUtils.GAMModelUtils

count - Variable in class hex.schemas.Word2VecSynonymsV3

COUNT - Static variable in class hex.tree.dt.mrtasks.CountBinsSamplesCountsMRTask

COUNT_0 - Static variable in class hex.tree.dt.mrtasks.CountBinsSamplesCountsMRTask

CountBinsSamplesCountsMRTask - Class in hex.tree.dt.mrtasks

MR task for counting samples in bins.

CountBinsSamplesCountsMRTask(int, double[][], double[][]) - Constructor for class hex.tree.dt.mrtasks.CountBinsSamplesCountsMRTask

countColNumber(String[][]) - Static method in class hex.anovaglm.GenerateTransformColumns

countNumConst(ComputationState) - Static method in class hex.glm.ConstrainedGLMUtils

CoxPH - Class in hex.coxph

Cox Proportional Hazards Model

CoxPH(boolean) - Constructor for class hex.coxph.CoxPH

CoxPH(CoxPHModel.CoxPHParameters) - Constructor for class hex.coxph.CoxPH

CoxPH.CoxPHDriver - Class in hex.coxph

CoxPH.CoxPHTask - Class in hex.coxph

CoxPHDriver() - Constructor for class hex.coxph.CoxPH.CoxPHDriver

CoxPHModel - Class in hex.coxph

CoxPHModel(Key, CoxPHModel.CoxPHParameters, CoxPHModel.CoxPHOutput) - Constructor for class hex.coxph.CoxPHModel

CoxPHModel.CoxPHOutput - Class in hex.coxph

CoxPHModel.CoxPHParameters - Class in hex.coxph

CoxPHModel.CoxPHParameters.CoxPHTies - Enum in hex.coxph

CoxPHModel.FrameMatrix - Class in hex.coxph

CoxPHModelOutputV3() - Constructor for class hex.schemas.CoxPHModelV3.CoxPHModelOutputV3

CoxPHModelV3 - Class in hex.schemas

CoxPHModelV3() - Constructor for class hex.schemas.CoxPHModelV3

CoxPHModelV3.CoxPHModelOutputV3 - Class in hex.schemas

CoxPHMojoWriter - Class in hex.coxph

CoxPHMojoWriter() - Constructor for class hex.coxph.CoxPHMojoWriter

CoxPHMojoWriter(CoxPHModel) - Constructor for class hex.coxph.CoxPHMojoWriter

CoxPHOutput(CoxPH, Frame, Frame, IcedHashMap<AstGroup.G, IcedInt>) - Constructor for class hex.coxph.CoxPHModel.CoxPHOutput

CoxPHParameters() - Constructor for class hex.coxph.CoxPHModel.CoxPHParameters

CoxPHParametersV3() - Constructor for class hex.schemas.CoxPHV3.CoxPHParametersV3

CoxPHV3 - Class in hex.schemas

CoxPHV3() - Constructor for class hex.schemas.CoxPHV3

CoxPHV3.CoxPHParametersV3 - Class in hex.schemas

createCenterTable(ClusteringModel.ClusteringOutput, boolean) - Static method in class hex.util.ClusteringUtils

createFrameOfExemplars(Frame, Key) - Method in class hex.aggregator.AggregatorModel

createGLMTrainFrame(Frame, int, int, String[], String, boolean) - Method in class hex.rulefit.RuleEnsemble

createImpl() - Method in class hex.schemas.AdaBoostModelV3

createImpl() - Method in class hex.schemas.AggregatorModelV99

createImpl() - Method in class hex.schemas.ANOVAGLMModelV3

createImpl() - Method in class hex.schemas.DeepLearningModelV3

createImpl() - Method in class hex.schemas.DRFModelV3

createImpl() - Method in class hex.schemas.DTModelV3

createImpl() - Method in class hex.schemas.ExtendedIsolationForestModelV3

createImpl() - Method in class hex.schemas.GAMModelV3

createImpl() - Method in class hex.schemas.GBMModelV3

createImpl() - Method in class hex.schemas.GLMModelV3

createImpl() - Method in class hex.schemas.GLRMModelV3

createImpl() - Method in class hex.schemas.GrepModelV3

createImpl() - Method in class hex.schemas.GrepModelV3.GrepModelOutputV3

createImpl() - Method in class hex.schemas.HGLMModelV3

createImpl() - Method in class hex.schemas.IsolationForestModelV3

createImpl() - Method in class hex.schemas.KMeansModelV3

createImpl() - Method in class hex.schemas.ModelSelectionModelV3

createImpl() - Method in class hex.schemas.NaiveBayesModelV3

createImpl() - Method in class hex.schemas.PCAModelV3

createImpl() - Method in class hex.schemas.PSVMModelV3

createImpl() - Method in class hex.schemas.RuleFitModelV3

createImpl() - Method in class hex.schemas.StackedEnsembleModelV99

createImpl() - Method in class hex.schemas.SVDModelV99

createImpl() - Method in class hex.schemas.UpliftDRFModelV3

createImpl() - Method in class hex.schemas.Word2VecModelV3

createInitialModelInfo(Word2VecModel.Word2VecParameters) - Static method in class hex.word2vec.Word2VecModel.Word2VecModelInfo

createInputFramesInformationTable(ModelBuilder) - Method in class hex.tree.SharedTreeModel.SharedTreeOutput

createMappingOfExemplars(Key) - Method in class hex.aggregator.AggregatorModel

createModelSummaryTable() - Method in class hex.adaboost.AdaBoost

createModelSummaryTable() - Method in class hex.tree.isoforextended.ExtendedIsolationForest

createModelSummaryTable(int, TreeStats) - Static method in class hex.tree.SharedTree

createOutputSchema() - Method in class hex.schemas.AdaBoostModelV3

createOutputSchema() - Method in class hex.schemas.AggregatorModelV99

createOutputSchema() - Method in class hex.schemas.ANOVAGLMModelV3

createOutputSchema() - Method in class hex.schemas.CoxPHModelV3

createOutputSchema() - Method in class hex.schemas.DeepLearningModelV3

createOutputSchema() - Method in class hex.schemas.DRFModelV3

createOutputSchema() - Method in class hex.schemas.DTModelV3

createOutputSchema() - Method in class hex.schemas.ExtendedIsolationForestModelV3

createOutputSchema() - Method in class hex.schemas.GAMModelV3

createOutputSchema() - Method in class hex.schemas.GBMModelV3

createOutputSchema() - Method in class hex.schemas.GenericModelV3

createOutputSchema() - Method in class hex.schemas.GLMModelV3

createOutputSchema() - Method in class hex.schemas.GLRMModelV3

createOutputSchema() - Method in class hex.schemas.GrepModelV3

createOutputSchema() - Method in class hex.schemas.HGLMModelV3

createOutputSchema() - Method in class hex.schemas.IsolationForestModelV3

createOutputSchema() - Method in class hex.schemas.IsotonicRegressionModelV3

createOutputSchema() - Method in class hex.schemas.KMeansModelV3

createOutputSchema() - Method in class hex.schemas.ModelSelectionModelV3

createOutputSchema() - Method in class hex.schemas.NaiveBayesModelV3

createOutputSchema() - Method in class hex.schemas.PCAModelV3

createOutputSchema() - Method in class hex.schemas.PSVMModelV3

createOutputSchema() - Method in class hex.schemas.RuleFitModelV3

createOutputSchema() - Method in class hex.schemas.StackedEnsembleModelV99

createOutputSchema() - Method in class hex.schemas.SVDModelV99

createOutputSchema() - Method in class hex.schemas.UpliftDRFModelV3

createOutputSchema() - Method in class hex.schemas.Word2VecModelV3

createParameters(String) - Static method in class hex.ensemble.Metalearners

createParametersSchema(String) - Static method in class hex.ensemble.Metalearners

createParametersSchema() - Method in class hex.schemas.AdaBoostModelV3

createParametersSchema() - Method in class hex.schemas.AggregatorModelV99

createParametersSchema() - Method in class hex.schemas.ANOVAGLMModelV3

createParametersSchema() - Method in class hex.schemas.CoxPHModelV3

createParametersSchema() - Method in class hex.schemas.DeepLearningModelV3

createParametersSchema() - Method in class hex.schemas.DRFModelV3

createParametersSchema() - Method in class hex.schemas.DTModelV3

createParametersSchema() - Method in class hex.schemas.ExtendedIsolationForestModelV3

createParametersSchema() - Method in class hex.schemas.GAMModelV3

createParametersSchema() - Method in class hex.schemas.GBMModelV3

createParametersSchema() - Method in class hex.schemas.GenericModelV3

createParametersSchema() - Method in class hex.schemas.GLMModelV3

createParametersSchema() - Method in class hex.schemas.GLRMModelV3

createParametersSchema() - Method in class hex.schemas.GrepModelV3

createParametersSchema() - Method in class hex.schemas.HGLMModelV3

createParametersSchema() - Method in class hex.schemas.IsolationForestModelV3

createParametersSchema() - Method in class hex.schemas.IsotonicRegressionModelV3

createParametersSchema() - Method in class hex.schemas.KMeansModelV3

createParametersSchema() - Method in class hex.schemas.ModelSelectionModelV3

createParametersSchema() - Method in class hex.schemas.NaiveBayesModelV3

createParametersSchema() - Method in class hex.schemas.PCAModelV3

createParametersSchema() - Method in class hex.schemas.PSVMModelV3

createParametersSchema() - Method in class hex.schemas.RuleFitModelV3

createParametersSchema() - Method in class hex.schemas.StackedEnsembleModelV99

createParametersSchema() - Method in class hex.schemas.SVDModelV99

createParametersSchema() - Method in class hex.schemas.UpliftDRFModelV3

createParametersSchema() - Method in class hex.schemas.Word2VecModelV3

createReverseSortedEigenpairs(double[], double[][]) - Static method in class hex.util.LinearAlgebraUtils

createScoringHistoryTable() - Method in class hex.tree.isofor.IsolationForest

createScoringHistoryTable(int) - Method in class hex.tree.isoforextended.ExtendedIsolationForest

createScoringHistoryTable() - Method in class hex.tree.SharedTree

createScoringHistoryTable(Model.Output, ScoreKeeper[], ScoreKeeper[], Job, long[], boolean, boolean) - Static method in class hex.tree.SharedTree

createScoringHistoryTable() - Method in class hex.tree.uplift.UpliftDRF

createScoringHistoryTableDR(LinkedHashMap<String, ArrayList>, String, long) - Static method in class hex.util.DimensionReductionUtils

Create the scoring history for dimension reduction algorithms like PCA/SVD.

createSortedEigenpairs(double[], double[][]) - Static method in class hex.util.LinearAlgebraUtils

ctree(int, int) - Method in class hex.tree.SharedTreeModel.SharedTreeOutput

CubicRegressionSplines - Class in hex.gam.GamSplines

CubicRegressionSplines(int, double[]) - Constructor for class hex.gam.GamSplines.CubicRegressionSplines

cv_canBuildMainModelInParallel() - Method in class hex.tree.SharedTree

cv_computeAndSetOptimalParameters(ModelBuilder[]) - Method in class hex.deeplearning.DeepLearning

cv_computeAndSetOptimalParameters(ModelBuilder[]) - Method in class hex.glm.GLM

If run with lambda search, we need to take extra action performed after cross-val models are built.

cv_computeAndSetOptimalParameters(ModelBuilder<M, P, O>[]) - Method in class hex.tree.SharedTree

cv_initStoppingParameters() - Method in class hex.tree.SharedTree

cv_makeAggregateModelMetrics(ModelMetrics.MetricBuilder[]) - Method in class hex.kmeans.KMeans

cv_updateOptimalParameters(ModelBuilder<M, P, O>[]) - Method in class hex.tree.SharedTree

D

d - Variable in class hex.schemas.SVDModelV99.SVDModelOutputV99

data(Chunk[], int, int) - Method in class hex.kmeans.KMeansModel

data_info - Variable in class hex.deeplearning.DeepLearningModelInfo

data_info() - Method in class hex.deeplearning.DeepLearningModelInfo

data_row(Chunk[], int, double[]) - Method in class hex.tree.SharedTree

DataFeaturesLimits - Class in hex.tree.dt

Features limits for the whole dataset.

DataFeaturesLimits(List<AbstractFeatureLimits>) - Constructor for class hex.tree.dt.DataFeaturesLimits

DataFeaturesLimits(double[][]) - Constructor for class hex.tree.dt.DataFeaturesLimits

DataInfo - Class in hex

Created by tomasnykodym on 1/29/15.

DataInfo(Frame, Frame, boolean, DataInfo.TransformType, boolean, boolean, boolean) - Constructor for class hex.DataInfo

DataInfo(Frame, Frame, int, boolean, DataInfo.TransformType, DataInfo.TransformType, boolean, boolean, boolean, boolean, boolean, boolean) - Constructor for class hex.DataInfo

DataInfo(Frame, Frame, int, boolean, DataInfo.TransformType, DataInfo.TransformType, boolean, boolean, boolean, boolean, boolean, boolean, Model.InteractionSpec) - Constructor for class hex.DataInfo

DataInfo(Frame, Frame, int, boolean, DataInfo.TransformType, DataInfo.TransformType, boolean, boolean, boolean, boolean, boolean, boolean, boolean, Model.InteractionSpec) - Constructor for class hex.DataInfo

DataInfo(Frame, Frame, int, boolean, DataInfo.TransformType, DataInfo.TransformType, boolean, boolean, DataInfo.Imputer, boolean, boolean, boolean, boolean, Model.InteractionSpec) - Constructor for class hex.DataInfo

DataInfo(Frame, Frame, int, boolean, DataInfo.TransformType, DataInfo.TransformType, boolean, boolean, DataInfo.Imputer, boolean, boolean, boolean, boolean, boolean, Model.InteractionSpec) - Constructor for class hex.DataInfo

The train/valid Frame instances are sorted by categorical (themselves sorted by cardinality greatest to least) with all numerical columns following.

DataInfo(Frame, Frame, int, boolean, DataInfo.TransformType, DataInfo.TransformType, boolean, boolean, boolean, boolean, boolean, boolean, boolean) - Constructor for class hex.DataInfo

DataInfo.Imputer - Interface in hex

DataInfo.MeanImputer - Class in hex

DataInfo.Row - Class in hex

DataInfo.Rows - Class in hex

DataInfo.TransformType - Enum in hex

DataInfoFrameV3 - Class in hex.schemas

DataInfoFrameV3() - Constructor for class hex.schemas.DataInfoFrameV3

decided(int) - Method in class hex.tree.DTree

DECIDED_ROW - Static variable in class hex.tree.ScoreBuildHistogram

Marker for already decided row.

DecidedNode(DTree.DecidedNode, DTree) - Constructor for class hex.tree.DTree.DecidedNode

DecidedNode(DTree.UndecidedNode, DHistogram[], Constraints, GlobalInteractionConstraints) - Constructor for class hex.tree.DTree.DecidedNode

decision_paths - Variable in class hex.schemas.TreeV3

decompose_2(double[][], int, int) - Static method in class hex.gram.Gram.InPlaceCholesky

deep_clone() - Method in class hex.gram.Gram

deepClone() - Method in class hex.DataInfo.Row

deepClone(Key<GLMModel>) - Method in class hex.glm.GLMModel

deepClone(Key<M>) - Method in class hex.tree.SharedTreeModel

Performs deep clone of given model.

DeepLearning - Class in hex.deeplearning

Deep Learning Neural Net implementation based on MRTask

DeepLearning(DeepLearningModel.DeepLearningParameters) - Constructor for class hex.deeplearning.DeepLearning

Main constructor from Deep Learning parameters

DeepLearning(DeepLearningModel.DeepLearningParameters, Key<DeepLearningModel>) - Constructor for class hex.deeplearning.DeepLearning

DeepLearning(boolean) - Constructor for class hex.deeplearning.DeepLearning

DeepLearning.DeepLearningDriver - Class in hex.deeplearning

DeepLearningDriver() - Constructor for class hex.deeplearning.DeepLearning.DeepLearningDriver

DeepLearningModel - Class in hex.deeplearning

The Deep Learning model It contains a DeepLearningModelInfo with the most up-to-date model, a scoring history, as well as some helpers to indicate the progress

DeepLearningModel(Key, DeepLearningModel.DeepLearningParameters, DeepLearningModel, boolean, DataInfo) - Constructor for class hex.deeplearning.DeepLearningModel

Constructor to restart from a checkpointed model

DeepLearningModel(Key, DeepLearningModel.DeepLearningParameters, DeepLearningModel.DeepLearningModelOutput, Frame, Frame, int) - Constructor for class hex.deeplearning.DeepLearningModel

Regular constructor (from scratch)

DeepLearningModel.DeepLearningModelOutput - Class in hex.deeplearning

The Deep Learning model output contains a few extra fields in addition to the metrics in Model.Output 1) Scoring history (raw data) 2) weights/biases (raw data) 3) variable importances (TwoDimTable)

DeepLearningModel.DeepLearningParameters - Class in hex.deeplearning

Deep Learning Parameters

DeepLearningModel.DeepLearningParameters.Activation - Enum in hex.deeplearning

Activation functions

DeepLearningModel.DeepLearningParameters.ClassSamplingMethod - Enum in hex.deeplearning

DeepLearningModel.DeepLearningParameters.InitialWeightDistribution - Enum in hex.deeplearning

DeepLearningModel.DeepLearningParameters.Loss - Enum in hex.deeplearning

Loss functions Absolute, Quadratic, Huber, Quantile for regression Quadratic, ModifiedHuber or CrossEntropy for classification

DeepLearningModel.DeepLearningParameters.MissingValuesHandling - Enum in hex.deeplearning

DeepLearningModelInfo - Class in hex.deeplearning

This class contains the state of the Deep Learning model This will be shared: one per node

DeepLearningModelInfo(DeepLearningModel.DeepLearningParameters, Key, DataInfo, int, Frame, Frame) - Constructor for class hex.deeplearning.DeepLearningModelInfo

Main constructor

DeepLearningModelInfo.GradientCheck - Class in hex.deeplearning

DeepLearningModelOutput(DeepLearning) - Constructor for class hex.deeplearning.DeepLearningModel.DeepLearningModelOutput

DeepLearningModelOutputV3() - Constructor for class hex.schemas.DeepLearningModelV3.DeepLearningModelOutputV3

DeepLearningModelV3 - Class in hex.schemas

DeepLearningModelV3() - Constructor for class hex.schemas.DeepLearningModelV3

DeepLearningModelV3.DeepLearningModelOutputV3 - Class in hex.schemas

DeepLearningMojoWriter - Class in hex.deeplearning

DeepLearningMojoWriter() - Constructor for class hex.deeplearning.DeepLearningMojoWriter

DeepLearningMojoWriter(DeepLearningModel) - Constructor for class hex.deeplearning.DeepLearningMojoWriter

DeepLearningParameters() - Constructor for class hex.deeplearning.DeepLearningModel.DeepLearningParameters

DeepLearningParametersV3() - Constructor for class hex.schemas.DeepLearningV3.DeepLearningParametersV3

DeepLearningScoringInfo - Class in hex.deeplearning

Lightweight DeepLearning scoring history.

DeepLearningScoringInfo() - Constructor for class hex.deeplearning.DeepLearningScoringInfo

DeepLearningTask - Class in hex.deeplearning

DeepLearningTask(Key, DeepLearningModelInfo, float, int) - Constructor for class hex.deeplearning.DeepLearningTask

The only constructor

DeepLearningTask(Key, DeepLearningModelInfo, float, int, H2O.H2OCountedCompleter) - Constructor for class hex.deeplearning.DeepLearningTask

DeepLearningTask2 - Class in hex.deeplearning

DRemoteTask-based Deep Learning.

DeepLearningTask2(Key, Frame, DeepLearningModelInfo, float, int) - Constructor for class hex.deeplearning.DeepLearningTask2

Construct a DeepLearningTask2 where every node trains on the entire training dataset

DeepLearningV3 - Class in hex.schemas

DeepLearningV3() - Constructor for class hex.schemas.DeepLearningV3

DeepLearningV3.DeepLearningParametersV3 - Class in hex.schemas

DEFAULT_ABSTOL - Static variable in class hex.optimization.ADMM.L1Solver

default_auuc_thresholds - Variable in class hex.schemas.UpliftDRFModelV3.UpliftDRFModelOutputV3

DEFAULT_RELTOL - Static variable in class hex.optimization.ADMM.L1Solver

defaultLink - Variable in enum hex.glm.GLMModel.GLMParameters.Family

defaultStoppingTolerance() - Method in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

defaultStoppingTolerance() - Method in class hex.tree.isofor.IsolationForestModel.IsolationForestParameters

defaultThreshold() - Method in class hex.generic.GenericModelOutput

defaultThreshold() - Method in class hex.tree.isofor.IsolationForestModel.IsolationForestOutput

deleteBaseModelPredictions() - Method in class hex.ensemble.StackedEnsembleModel

deleteCrossValidationFoldAssignment() - Method in class hex.ensemble.StackedEnsembleModel

deleteCrossValidationModels() - Method in class hex.ensemble.StackedEnsembleModel

deleteCrossValidationPreds() - Method in class hex.ensemble.StackedEnsembleModel

denNA() - Method in class hex.tree.DHistogram

denormalizeBeta(double[]) - Method in class hex.DataInfo

derivativeCoeffs(double[][]) - Static method in class hex.gam.GamSplines.NBSplinesTypeIDerivative

descriptions - Variable in class hex.schemas.TreeV3

desiredChunks(Frame, boolean) - Method in class hex.deeplearning.DeepLearning

dest - Variable in class hex.schemas.MakeGLMModelV3

destination_frame - Variable in class hex.schemas.GramV3

dev - Variable in class hex.glm.GLMModel.GLMWeights

deviance() - Method in class hex.glm.ComputationState

deviance(double, double, double) - Method in class hex.glm.GLMModel

deviance(double, double) - Method in class hex.glm.GLMModel.GLMParameters

deviance(float, float) - Method in class hex.glm.GLMModel.GLMParameters

deviance(double, double) - Method in class hex.glm.GLMModel.GLMWeightsFun

deviance(float, float) - Method in class hex.glm.GLMModel.GLMWeightsFun

deviance(double, double, double) - Static method in class hex.glm.TweedieEstimator

devianceTrain - Variable in class hex.glm.GLMModel.Submodel

devianceValid - Variable in class hex.glm.GLMModel.Submodel

DHistogram - Class in hex.tree

A Histogram, computed in parallel over a Vec.

DHistogram.NASplitDir - Enum in hex.tree

Split direction for missing values.

DhnasdLeft - Static variable in class hex.tree.TreeVisitor

DhnasdNaLeft - Static variable in class hex.tree.TreeVisitor

DhnasdNaVsRest - Static variable in class hex.tree.TreeVisitor

diagnostics - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

Gather diagnostics for hidden layers, such as mean and RMS values of learning rate, momentum, weights and biases.

diagSum() - Method in class hex.gram.Gram

DiffMinusMedianDiff(Vec, double[]) - Constructor for class hex.tree.gbm.GBM.DiffMinusMedianDiff

DimensionReductionUtils - Class in hex.util

Created by wendycwong on 2/9/17.

DimensionReductionUtils() - Constructor for class hex.util.DimensionReductionUtils

dinfo() - Method in class hex.FrameTask

dinfo() - Method in class hex.glm.GLMModel

disable_training_metrics - Variable in class hex.schemas.ExtendedIsolationForestV3.ExtendedIsolationForestParametersV3

disable_training_metrics - Variable in class hex.schemas.PSVMV3.PSVMParametersV3

disableIntercept() - Method in class hex.DataInfo

dispersion() - Method in class hex.glm.GLMModel.GLMOutput

dispersion_epsilon - Variable in class hex.schemas.GLMV3.GLMParametersV3

dispersion_learning_rate - Variable in class hex.schemas.GLMV3.GLMParametersV3

dispersion_parameter_method - Variable in class hex.schemas.GLMV3.GLMParametersV3

dispersionEstimated() - Method in class hex.glm.ComputationState

dispersionEstimated() - Method in class hex.glm.GLMModel.GLMOutput

dispersionEstimated - Variable in class hex.glm.GLMModel.Submodel

dispersionLS(DispersionTask.ComputeMaxSumSeriesTsk, TweedieMLDispersionOnly, GLMModel.GLMParameters) - Static method in class hex.glm.DispersionUtils

DispersionTask - Class in hex.glm

DispersionTask() - Constructor for class hex.glm.DispersionTask

DispersionTask.ComputeMaxSumSeriesTsk - Class in hex.glm

This class will compute the following for every row of the dataset: 1.

DispersionTask.ComputeMaxSumSeriesTsk.CalWVdWVd2WV - Interface in hex.glm

This interface is used to calculate one item of the series in log.

DispersionTask.ComputeMaxSumSeriesTsk.EvalLogD2WVEnv - Class in hex.glm

DispersionTask.ComputeMaxSumSeriesTsk.EvalLogDWVEnv - Class in hex.glm

DispersionTask.ComputeMaxSumSeriesTsk.EvalLogWVEnv - Class in hex.glm

DispersionTask.ComputeTweedieConstTsk - Class in hex.glm

Class to pre-calculate constants assocated with the following processes: 1.

DispersionTask.ConstColNames - Enum in hex.glm

DispersionTask.GenPrediction - Class in hex.glm

DispersionTask.InfoColNames - Enum in hex.glm

DispersionUtils - Class in hex.glm

DispersionUtils() - Constructor for class hex.glm.DispersionUtils

distributionToFamily(DistributionFamily) - Static method in class hex.util.DistributionUtils

DistributionUtils - Class in hex.util

DistributionUtils() - Constructor for class hex.util.DistributionUtils

div(double) - Method in class hex.deeplearning.DeepLearningModelInfo

Divide all weights/biases by a real-valued number

Divergence - Class in hex.tree.uplift

Divergence class used to calculate gain to split the node in Uplift trees algorithms.

Divergence() - Constructor for class hex.tree.uplift.Divergence

doInTrainingCheckpoint() - Method in class hex.tree.SharedTree.Driver

doModelSpecificComputation(float[]) - Method in class hex.tree.drf.DRFModel.ScoreContributionsSoringTaskDRF

doModelSpecificComputation(double[]) - Method in class hex.tree.drf.DRFModel.ScoreContributionsWithBackgroundTaskDRF

doModelSpecificComputation(float[]) - Method in class hex.tree.SharedTreeModelWithContributions.ScoreContributionsTask

doModelSpecificComputation(double[]) - Method in class hex.tree.SharedTreeModelWithContributions.ScoreContributionsWithBackgroundTask

doNotSplit() - Method in class hex.tree.DTree.UndecidedNode

doOOBScoring() - Method in class hex.tree.SharedTree.Driver

doScoringAndSaveModel(boolean, boolean, boolean) - Method in class hex.tree.SharedTree

dotSame(DataInfo.Row) - Method in class hex.DataInfo.Row

DRF - Class in hex.tree.drf

Distributed Random Forest

DRF(DRFModel.DRFParameters) - Constructor for class hex.tree.drf.DRF

DRF(DRFModel.DRFParameters, Key<DRFModel>) - Constructor for class hex.tree.drf.DRF

DRF(DRFModel.DRFParameters, Job) - Constructor for class hex.tree.drf.DRF

DRF(boolean) - Constructor for class hex.tree.drf.DRF

DRFModel - Class in hex.tree.drf

DRFModel(Key<DRFModel>, DRFModel.DRFParameters, DRFModel.DRFOutput) - Constructor for class hex.tree.drf.DRFModel

DRFModel.DRFOutput - Class in hex.tree.drf

DRFModel.DRFParameters - Class in hex.tree.drf

DRFModel.ScoreContributionsSoringTaskDRF - Class in hex.tree.drf

DRFModel.ScoreContributionsTaskDRF - Class in hex.tree.drf

DRFModel.ScoreContributionsWithBackgroundTaskDRF - Class in hex.tree.drf

DRFModelOutputV3() - Constructor for class hex.schemas.DRFModelV3.DRFModelOutputV3

DRFModelV3 - Class in hex.schemas

DRFModelV3() - Constructor for class hex.schemas.DRFModelV3

DRFModelV3.DRFModelOutputV3 - Class in hex.schemas

DrfMojoWriter - Class in hex.tree.drf

Mojo definition for DRF model.

DrfMojoWriter() - Constructor for class hex.tree.drf.DrfMojoWriter

DrfMojoWriter(DRFModel) - Constructor for class hex.tree.drf.DrfMojoWriter

DRFOutput(DRF) - Constructor for class hex.tree.drf.DRFModel.DRFOutput

DRFParameters() - Constructor for class hex.tree.drf.DRFModel.DRFParameters

DRFParametersV3() - Constructor for class hex.schemas.DRFV3.DRFParametersV3

DRFV3 - Class in hex.schemas

DRFV3() - Constructor for class hex.schemas.DRFV3

DRFV3.DRFParametersV3 - Class in hex.schemas

Driver() - Constructor for class hex.tree.SharedTree.Driver

dropActiveData() - Method in class hex.glm.ComputationState

dropCols(int[], double[][]) - Static method in class hex.glm.ComputationState.GramGrad

dropCols(int[]) - Method in class hex.gram.Gram

dropIgnoredCols(double[][], double[][], List<Integer>) - Static method in class hex.glm.ComputationState.GramGrad

dropIgnoredCols(GLMTask.GLMIterationTask, List<Integer>) - Static method in class hex.modelselection.ModelSelectionUtils

dropInteractions() - Method in class hex.DataInfo

dropIntercept() - Method in class hex.gram.Gram

Dropout - Class in hex.deeplearning

Helper class for dropout training of Neural Nets

dropWeights() - Method in class hex.DataInfo

DT - Class in hex.tree.dt

Decision Tree

DT(DTModel.DTParameters) - Constructor for class hex.tree.dt.DT

DT(boolean) - Constructor for class hex.tree.dt.DT

DTModel - Class in hex.tree.dt

DTModel(Key<DTModel>, DTModel.DTParameters, DTModel.DTOutput) - Constructor for class hex.tree.dt.DTModel

DTModel.DTOutput - Class in hex.tree.dt

DTModel.DTParameters - Class in hex.tree.dt

DTModelOutputV3() - Constructor for class hex.schemas.DTModelV3.DTModelOutputV3

DTModelV3 - Class in hex.schemas

DTModelV3() - Constructor for class hex.schemas.DTModelV3

DTModelV3.DTModelOutputV3 - Class in hex.schemas

DTOutput(DT) - Constructor for class hex.tree.dt.DTModel.DTOutput

DTParameters() - Constructor for class hex.tree.dt.DTModel.DTParameters

DTParametersV3() - Constructor for class hex.schemas.DTV3.DTParametersV3

DTPrediction - Class in hex.tree.dt

DTPrediction(int, double, String) - Constructor for class hex.tree.dt.DTPrediction

DTree - Class in hex.tree

A Decision Tree, laid over a Frame of Vecs, and built distributed.

DTree(Frame, int, int, int, long, SharedTreeModel.SharedTreeParameters) - Constructor for class hex.tree.DTree

DTree(DTree) - Constructor for class hex.tree.DTree

Copy constructor

DTree.DecidedNode - Class in hex.tree

DTree.DecidedNode.FindSplits - Class in hex.tree

DTree.LeafNode - Class in hex.tree

DTree.Node - Class in hex.tree

DTree.Split - Class in hex.tree

DTree.UndecidedNode - Class in hex.tree

DTreeScorer<T extends DTreeScorer<T>> - Class in hex.tree

DTreeScorer(int, int, SharedTree, CompressedForest) - Constructor for class hex.tree.DTreeScorer

DTV3 - Class in hex.schemas

DTV3() - Constructor for class hex.schemas.DTV3

DTV3.DTParametersV3 - Class in hex.schemas

E

early_stopping - Variable in class hex.schemas.ANOVAGLMV3.ANOVAGLMParametersV3

early_stopping - Variable in class hex.schemas.GAMV3.GAMParametersV3

early_stopping - Variable in class hex.schemas.GLMV3.GLMParametersV3

early_stopping - Variable in class hex.schemas.ModelSelectionV3.ModelSelectionParametersV3

EffectiveParametersUtils - Class in hex.util

EffectiveParametersUtils() - Constructor for class hex.util.EffectiveParametersUtils

EigenPair - Class in hex.util

EigenPair(double, double[]) - Constructor for class hex.util.EigenPair

eigenvalue - Variable in class hex.util.EigenPair

eigenvector - Variable in class hex.util.EigenPair

eigenvectors - Variable in class hex.schemas.GLRMModelV3.GLRMModelOutputV3

eigenvectors - Variable in class hex.schemas.PCAModelV3.PCAModelOutputV3

elastic_averaging - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

elastic_averaging_moving_rate - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

elastic_averaging_regularization - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

elasticAverageModelInfoKey() - Method in class hex.deeplearning.DeepLearningModelInfo

em_epsilon - Variable in class hex.schemas.HGLMV3.HGLMParametersV3

enoughMinMemory(double) - Static method in class hex.ContributionsWithBackgroundFrameTask

entropyBinarySplit(double) - Static method in class hex.tree.dt.binning.SplitStatistics

epoch_counter - Variable in class hex.deeplearning.DeepLearningModel

epoch_counter - Variable in class hex.deeplearning.DeepLearningScoringInfo

epoch_counter() - Method in class hex.deeplearning.DeepLearningScoringInfo

epochs - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

The number of passes over the training dataset to be carried out.

epochs - Variable in class hex.schemas.Word2VecModelV3.Word2VecModelOutputV3

epochs - Variable in class hex.schemas.Word2VecV3.Word2VecParametersV3

EPS - Static variable in class hex.gam.MatrixFrameUtils.GamUtils

EPS - Static variable in class hex.glm.ConstrainedGLMUtils

EPS2 - Static variable in class hex.glm.ConstrainedGLMUtils

EPS_CS - Static variable in class hex.glm.ComputationState

EPS_CS_SQUARE - Static variable in class hex.glm.ComputationState

eps_prob - Variable in class hex.schemas.NaiveBayesV3.NaiveBayesParametersV3

eps_sdev - Variable in class hex.schemas.NaiveBayesV3.NaiveBayesParametersV3

epsilon - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

The second of two hyper parameters for adaptive learning rate (ADADELTA).

EPSILON - Static variable in class hex.tree.dt.DT

equal2DArrays(double[][], double[][], double) - Static method in class hex.hglm.HGLMUtils

equalColNames(String[], String[], String) - Static method in class hex.gam.MatrixFrameUtils.GamUtils

equals(Object) - Method in class hex.glm.ConstrainedGLMUtils.CoefIndices

equals(Object) - Method in class hex.rulefit.Condition

equals(Object) - Method in class hex.rulefit.Rule

equals(AbstractFeatureLimits) - Method in class hex.tree.dt.AbstractFeatureLimits

equals(AbstractFeatureLimits) - Method in class hex.tree.dt.CategoricalFeatureLimits

equals(DataFeaturesLimits) - Method in class hex.tree.dt.DataFeaturesLimits

equals(AbstractFeatureLimits) - Method in class hex.tree.dt.NumericFeatureLimits

equals(Object) - Method in class hex.tree.SharedTree.SharedTreeDebugParams

estimate_k - Variable in class hex.schemas.KMeansV3.KMeansParametersV3

estimateFixedCoeff(double[][], double[], double[][][], double[][]) - Static method in class hex.hglm.HGLMUtils

estimateGammaMLSE(GLMTask.ComputeGammaMLSETsk, double, double[], GLMModel.GLMParameters, ComputationState, Job, GLMModel) - Static method in class hex.glm.DispersionUtils

Estimate dispersion factor using maximum likelihood.

estimateLowerBound(int, double, double, DispersionTask.ComputeMaxSumSeriesTsk.CalWVdWVd2WV) - Method in class hex.glm.DispersionTask.ComputeMaxSumSeriesTsk

estimateNegBinomialDispersionFisherScoring(GLMModel.GLMParameters, GLMModel, double[], DataInfo) - Static method in class hex.glm.DispersionUtils

estimateNegBinomialDispersionMomentMethod(GLMModel, double[], DataInfo, Vec, Vec, Vec) - Static method in class hex.glm.DispersionUtils

estimateNewRandomEffects(double[][][], double[][], double[][][], double[]) - Static method in class hex.hglm.HGLMUtils

Note that the term ArjTYj and ArjTAfj are fixed and won't change.

estimateNewtMat(double[][], double, double[][][], double) - Static method in class hex.hglm.HGLMUtils

estimatePerNodeMinimalMemory(int, Frame, Frame) - Static method in class hex.ContributionsWithBackgroundFrameTask

estimateRequiredMemory(int, Frame, Frame) - Static method in class hex.ContributionsWithBackgroundFrameTask

estimateRho(double, double, double, double) - Static method in class hex.optimization.ADMM.L1Solver

Estimate optimal rho based on l1 penalty and (estimate of) solution x without the l1penalty

estimateTweedieDispersionOnly(GLMModel.GLMParameters, GLMModel, Job, double[], DataInfo) - Static method in class hex.glm.DispersionUtils

This method estimates the tweedie dispersion parameter.

estimateUpperBound(int, double, double, int, DispersionTask.ComputeMaxSumSeriesTsk.CalWVdWVd2WV) - Method in class hex.glm.DispersionTask.ComputeMaxSumSeriesTsk

EuclideanDistance - Class in hex.tree.uplift

EuclideanDistance() - Constructor for class hex.tree.uplift.EuclideanDistance

evalD2lldPhi2(Chunk[], int, double, double, double, Map<DispersionTask.ConstColNames, Integer>) - Method in class hex.glm.DispersionTask.ComputeMaxSumSeriesTsk

evalDlldPhi(Chunk[], int, double, double, Map<DispersionTask.ConstColNames, Integer>) - Method in class hex.glm.DispersionTask.ComputeMaxSumSeriesTsk

EvalLogD2WVEnv() - Constructor for class hex.glm.DispersionTask.ComputeMaxSumSeriesTsk.EvalLogD2WVEnv

EvalLogDWVEnv() - Constructor for class hex.glm.DispersionTask.ComputeMaxSumSeriesTsk.EvalLogDWVEnv

evalLogLikelihood(Chunk[], int, double, Map<DispersionTask.ConstColNames, Integer>) - Method in class hex.glm.DispersionTask.ComputeMaxSumSeriesTsk

EvalLogWVEnv() - Constructor for class hex.glm.DispersionTask.ComputeMaxSumSeriesTsk.EvalLogWVEnv

evalOneConstraint(ConstrainedGLMUtils.LinearConstraints, double[], List<String>) - Static method in class hex.glm.ConstrainedGLMUtils

This method will evaluate the value of a constraint given the GLM coefficients and the coefficicent name list.

evaluate(double[]) - Method in interface hex.optimization.OptimizationUtils.LineSearchSolver

evaluate(double[]) - Method in class hex.optimization.OptimizationUtils.MoreThuente

evaluate(double[]) - Method in class hex.optimization.OptimizationUtils.SimpleBacktrackingLS

evaluateConstraint(ComputationState, ConstrainedGLMUtils.LinearConstraints[], boolean, double[], List<String>, String, List<String>, List<String>, List<Double>, List<String>, List<String>) - Static method in class hex.glm.ConstrainedGLMUtils

Print constraints without any standardization applied so that people can see the setting in their original form without standardization.

evaluateFirstWolfe(GLM.GLMGradientInfo) - Method in class hex.optimization.OptimizationUtils.ExactLineSearch

Evaluate and make sure that step size alphi is not too big so that objective function is still decreasing.

evaluateSecondWolfe(GLM.GLMGradientInfo) - Method in class hex.optimization.OptimizationUtils.ExactLineSearch

Evaluate and make sure that step size alphi is not too small so that good progress is made in reducing the loss function.

ExactLineSearch(double[], ComputationState, List<String>) - Constructor for class hex.optimization.OptimizationUtils.ExactLineSearch

ExactSplitPoints - Class in hex.tree

Finds exact split points for low-cardinality columns.

expand(Frame, Model.InteractionSpec, boolean, boolean, boolean) - Static method in class hex.glm.GLMModel.GLMOutput

expand_user_y - Variable in class hex.schemas.GLRMV3.GLRMParametersV3

expandBeta(double[]) - Method in class hex.glm.ComputationState

expandCats() - Method in class hex.DataInfo.Row

expandCats(double[][], DataInfo) - Static method in class hex.glrm.GLRM

expandCatsPredsOnly(double[]) - Method in class hex.DataInfo.Row

expandCombo(int[], int[], Integer[]) - Static method in class hex.gam.GamSplines.ThinPlateRegressionUtils

Given a combo found by findOnePerm say for d = 5, m = 4, for degree = 1 to m-1 (3 in this case).

expandedCatCS(Frame, GLMModel.GLMParameters) - Static method in class hex.glm.GLMUtils

expandLowTrian2Ful(double[][]) - Static method in class hex.util.LinearAlgebraUtils

expandRow(double[], DataInfo, double[], boolean) - Static method in class hex.util.LinearAlgebraUtils

expandToFullArray(double[], int[], int, int, int) - Static method in class hex.glm.ComputationState

explained_deviance_train - Variable in class hex.schemas.GLMRegularizationPathV3

explained_deviance_valid - Variable in class hex.schemas.GLMRegularizationPathV3

explainedDev() - Method in class hex.glm.GLMMetricBuilder

export_weights_and_biases - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

ExpRectifier(int) - Constructor for class hex.deeplearning.Neurons.ExpRectifier

ExpRectifierDropout(int) - Constructor for class hex.deeplearning.Neurons.ExpRectifierDropout

extendCoeffNames(String[], int) - Static method in class hex.schemas.HGLMModelV3

ExtendedIsolationForest - Class in hex.tree.isoforextended

Extended isolation forest implementation.

ExtendedIsolationForest(ExtendedIsolationForestModel.ExtendedIsolationForestParameters) - Constructor for class hex.tree.isoforextended.ExtendedIsolationForest

ExtendedIsolationForest(ExtendedIsolationForestModel.ExtendedIsolationForestParameters, Key<ExtendedIsolationForestModel>) - Constructor for class hex.tree.isoforextended.ExtendedIsolationForest

ExtendedIsolationForest(ExtendedIsolationForestModel.ExtendedIsolationForestParameters, Job) - Constructor for class hex.tree.isoforextended.ExtendedIsolationForest

ExtendedIsolationForest(boolean) - Constructor for class hex.tree.isoforextended.ExtendedIsolationForest

ExtendedIsolationForestModel - Class in hex.tree.isoforextended

ExtendedIsolationForestModel(Key<ExtendedIsolationForestModel>, ExtendedIsolationForestModel.ExtendedIsolationForestParameters, ExtendedIsolationForestModel.ExtendedIsolationForestOutput) - Constructor for class hex.tree.isoforextended.ExtendedIsolationForestModel

ExtendedIsolationForestModel.ExtendedIsolationForestOutput - Class in hex.tree.isoforextended

ExtendedIsolationForestModel.ExtendedIsolationForestParameters - Class in hex.tree.isoforextended

ExtendedIsolationForestModelOutputV3() - Constructor for class hex.schemas.ExtendedIsolationForestModelV3.ExtendedIsolationForestModelOutputV3

ExtendedIsolationForestModelV3 - Class in hex.schemas

ExtendedIsolationForestModelV3() - Constructor for class hex.schemas.ExtendedIsolationForestModelV3

ExtendedIsolationForestModelV3.ExtendedIsolationForestModelOutputV3 - Class in hex.schemas

ExtendedIsolationForestMojoWriter - Class in hex.tree.isoforextended

ExtendedIsolationForestMojoWriter() - Constructor for class hex.tree.isoforextended.ExtendedIsolationForestMojoWriter

ExtendedIsolationForestMojoWriter(ExtendedIsolationForestModel) - Constructor for class hex.tree.isoforextended.ExtendedIsolationForestMojoWriter

ExtendedIsolationForestOutput(ExtendedIsolationForest) - Constructor for class hex.tree.isoforextended.ExtendedIsolationForestModel.ExtendedIsolationForestOutput

ExtendedIsolationForestParameters() - Constructor for class hex.tree.isoforextended.ExtendedIsolationForestModel.ExtendedIsolationForestParameters

ExtendedIsolationForestParametersV3() - Constructor for class hex.schemas.ExtendedIsolationForestV3.ExtendedIsolationForestParametersV3

extendedIsolationForestSplit(double[][], double[], double[]) - Static method in class hex.tree.isoforextended.isolationtree.IsolationTree

Compute Extended Isolation Forest split point and filter input data with this split point in the same time.

ExtendedIsolationForestV3 - Class in hex.schemas

ExtendedIsolationForestV3() - Constructor for class hex.schemas.ExtendedIsolationForestV3

ExtendedIsolationForestV3.ExtendedIsolationForestParametersV3 - Class in hex.schemas

extendLevel2Ind(String[], int) - Static method in class hex.schemas.HGLMModelV3

extension_level - Variable in class hex.schemas.ExtendedIsolationForestV3.ExtendedIsolationForestParametersV3

extractAdaptedFrameIndices(Frame, String[][], int) - Static method in class hex.glm.GLMUtils

From the gamColnames, this method attempts to translate to the column indices in adaptFrame.

extractBetaConstraints(ComputationState, String[]) - Static method in class hex.glm.ConstrainedGLMUtils

This method will extract the constraints specified in beta constraint and combine it with the linear constraints later.

extractCoeffNames(List<String>, ConstrainedGLMUtils.LinearConstraints[]) - Static method in class hex.glm.ConstrainedGLMUtils

extractCoefsFromPred(List<String>, boolean, DataInfo, int[]) - Static method in class hex.modelselection.ModelSelectionModel.ModelSelectionModelOutput

extractCoefsValues(double[][], int, boolean, int, ModelSelectionUtils.CoeffNormalization, int, int[], int[][]) - Method in class hex.modelselection.ModelSelectionModel.ModelSelectionModelOutput

extractColNames(String[], int, int, int) - Static method in class hex.gam.GamSplines.ThinPlateRegressionUtils

extractCompressedTrees(SharedTreeMojoModel) - Static method in class hex.tree.MojoUtils

extractConstraint(Frame, List<Integer>, List<ConstrainedGLMUtils.LinearConstraints>, DataInfo, List<String>, List<String>) - Static method in class hex.glm.ConstrainedGLMUtils

extractConstraintCoeffs(ComputationState) - Static method in class hex.glm.ConstrainedGLMUtils

extractConstraintValues(ConstrainedGLMUtils.LinearConstraints[], List<String>, double[][], int, int[]) - Static method in class hex.glm.ConstrainedGLMUtils

extractCPMIndexFromPred(int, int[][], int[], boolean) - Static method in class hex.modelselection.ModelSelectionUtils

extractCPMIndexFromPredOnly(int[][], int[]) - Static method in class hex.modelselection.ModelSelectionUtils

Given the predictor in subset newPredList, this function will find the rows/columns in the cpm matrix that are contributed by the predictors in subset newPredList.

extractDenseRow(Chunk[], int, DataInfo.Row) - Method in class hex.DataInfo

ExtractDenseRow(DataInfo, long) - Constructor for class hex.FrameTask.ExtractDenseRow

extractDerivativeCoeff(NBSplinesTypeI, NBSplinesTypeI, double[], int, double) - Static method in class hex.gam.GamSplines.NBSplinesTypeIDerivative

This function extracts the coefficients for the derivative of a NBSplineTypeI (Mi,k(t)) as described in Section VI of doc.

extractEigenvaluesFromEigenpairs(EigenPair[]) - Static method in class hex.util.LinearAlgebraUtils

extractEigenvectorsFromEigenpairs(EigenPair[]) - Static method in class hex.util.LinearAlgebraUtils

extractGLMModels(GLM[]) - Static method in class hex.anovaglm.ANOVAGLMUtils

Simple method to extract GLM Models from GLM ModelBuilders.

extractLinearConstraints(ComputationState, Key<Frame>, DataInfo) - Static method in class hex.glm.ConstrainedGLMUtils

This method will extract the constraints specified in the Frame with key linearConstraintFrameKey.

extractNDemeanOneRowFromChunk(Chunk[], int, double[], int) - Static method in class hex.gam.GamSplines.ThinPlatePolynomialWithKnots

extractPredictorNames(Model.Parameters, DataInfo, String) - Static method in class hex.modelselection.ModelSelectionUtils

extractPredNames(DataInfo, int) - Static method in class hex.anovaglm.ANOVAGLMUtils

This method will extract the individual predictor names that will be used to build the GLM models.

extractPredsFromPredIndices(String[], int[]) - Static method in class hex.modelselection.ModelSelectionModel.ModelSelectionModelOutput

extractPredSubsetsCPM(double[][], int[], int[][], boolean) - Static method in class hex.modelselection.ModelSelectionUtils

Given a predictor subset and the complete CPM, we extract the CPM associated with the predictors specified in the predictor subset (predIndices).

extractPredSubsetsCPMFrame(Frame, int[], int[][], boolean) - Static method in class hex.modelselection.ModelSelectionUtils

Given a predictor subset and the complete CPM, we extract the CPM associated with the predictors specified in the predictor subset (predIndices).

extractRegularizationPath(int, GLMRegularizationPathV3) - Method in class hex.api.MakeGLMModelHandler

extractRulesFromTree(SharedTreeSubgraph, int, String) - Static method in class hex.rulefit.Rule

extractRulesListFromModel(SharedTreeModel, int, int) - Static method in class hex.rulefit.Rule

extractRulesStartingWithNode(int, String, int) - Method in class hex.tree.dt.CompressedDT

extractSparseRows(Chunk[]) - Method in class hex.DataInfo

Extract (sparse) rows from given chunks.

extractSubRange(int, int, int[], double[]) - Static method in class hex.glm.ComputationState

This method will return a double array that is extracted from src (which includes active and non-active columns) to only include active columns stated in ids.

extractSweepIndices(List<Integer>, int, int, int[][], boolean) - Static method in class hex.modelselection.ModelSelectionUtils

Given predRemoved (the predictor that is to be removed and replaced in the forward step), this method will calculate the locations of the CPM rows/columns associated with it.

extractVec2List(Frame) - Method in class hex.glm.GLM.BetaConstraint

Extract predictor names in the constraint frame constraintF into a list.

extraModelColumnNames(List<String>, GLMModel) - Static method in class hex.modelselection.ModelSelectionUtils

extraMojoFeatures() - Method in class hex.coxph.CoxPHModel

F

fact_threshold - Variable in class hex.schemas.PSVMV3.PSVMParametersV3

failVerifyKnots(double[], int) - Method in class hex.gam.GAM

family - Variable in class hex.schemas.ANOVAGLMV3.ANOVAGLMParametersV3

family - Variable in class hex.schemas.GAMV3.GAMParametersV3

family - Variable in class hex.schemas.GLMV3.GLMParametersV3

family - Variable in class hex.schemas.HGLMV3.HGLMParametersV3

family - Variable in class hex.schemas.ModelSelectionV3.ModelSelectionParametersV3

familyToDistribution(GLMModel.GLMParameters.Family) - Static method in class hex.util.DistributionUtils

fast_mode - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

Enable fast mode (minor approximation in back-propagation), should not affect results significantly.

feasible_threshold - Variable in class hex.schemas.PSVMV3.PSVMParametersV3

FeatureBins - Class in hex.tree.dt.binning

FeatureBins(List<AbstractBin>) - Constructor for class hex.tree.dt.binning.FeatureBins

FeatureBins(List<AbstractBin>, int) - Constructor for class hex.tree.dt.binning.FeatureBins

featureName - Variable in class hex.rulefit.Condition

features - Variable in class hex.schemas.TreeV3

featuresCount() - Method in class hex.tree.dt.binning.Histogram

featuresCount() - Method in class hex.tree.dt.DataFeaturesLimits

Get count of features.

FeaturesLimitsMRTask - Class in hex.tree.dt.mrtasks

MR task for calculating real features limits based on limits.

FeaturesLimitsMRTask(double[][]) - Constructor for class hex.tree.dt.mrtasks.FeaturesLimitsMRTask

fetch() - Method in class hex.tree.CompressedForest

Fetches trees from DKV and converts to a node-local structure.

fields - Static variable in class hex.schemas.AdaBoostV3.AdaBoostParametersV3

fields - Static variable in class hex.schemas.AggregatorV99.AggregatorParametersV99

fields - Static variable in class hex.schemas.ANOVAGLMV3.ANOVAGLMParametersV3

fields - Static variable in class hex.schemas.CoxPHV3.CoxPHParametersV3

fields - Static variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

fields - Static variable in class hex.schemas.DRFV3.DRFParametersV3

fields - Static variable in class hex.schemas.DTV3.DTParametersV3

fields - Static variable in class hex.schemas.ExtendedIsolationForestV3.ExtendedIsolationForestParametersV3

fields - Static variable in class hex.schemas.GAMV3.GAMParametersV3

fields - Static variable in class hex.schemas.GBMV3.GBMParametersV3

fields - Static variable in class hex.schemas.GenericV3.GenericParametersV3

fields - Static variable in class hex.schemas.GLMV3.GLMParametersV3

fields - Static variable in class hex.schemas.GLRMV3.GLRMParametersV3

fields - Static variable in class hex.schemas.HGLMV3.HGLMParametersV3

fields - Static variable in class hex.schemas.IsolationForestV3.IsolationForestParametersV3

fields - Static variable in class hex.schemas.IsotonicRegressionV3.IsotonicRegressionParametersV3

fields - Static variable in class hex.schemas.KMeansV3.KMeansParametersV3

fields - Static variable in class hex.schemas.ModelSelectionV3.ModelSelectionParametersV3

fields - Static variable in class hex.schemas.NaiveBayesV3.NaiveBayesParametersV3

fields - Static variable in class hex.schemas.PCAV3.PCAParametersV3

fields - Static variable in class hex.schemas.PSVMV3.PSVMParametersV3

fields - Static variable in class hex.schemas.RuleFitV3.RuleFitParametersV3

fields - Static variable in class hex.schemas.StackedEnsembleV99.StackedEnsembleParametersV99

fields - Static variable in class hex.schemas.SVDV99.SVDParametersV99

fields - Static variable in class hex.schemas.UpliftDRFV3.UpliftDRFParametersV3

fields - Static variable in class hex.schemas.Word2VecV3.Word2VecParametersV3

fillBytes(long) - Method in class hex.deeplearning.Dropout

fillConstraintValues(ComputationState, List<String>, double[][], int[]) - Static method in class hex.glm.ConstrainedGLMUtils

fillFromImpl(ANOVAGLMModel.ANOVAGLMModelOutput) - Method in class hex.schemas.ANOVAGLMModelV3.ANOVAGLMModelOutputV3

fillFromImpl(CoxPHModel.CoxPHOutput) - Method in class hex.schemas.CoxPHModelV3.CoxPHModelOutputV3

fillFromImpl(GenericModelParameters, String[]) - Method in class hex.schemas.GenericV3.GenericParametersV3

fillFromImpl(GenericModelParameters) - Method in class hex.schemas.GenericV3.GenericParametersV3

fillFromImpl(GLMModel.GLMOutput) - Method in class hex.schemas.GLMModelV3.GLMModelOutputV3

fillFromImpl(GrepModel) - Method in class hex.schemas.GrepModelV3

fillFromImpl(GrepModel.GrepOutput) - Method in class hex.schemas.GrepModelV3.GrepModelOutputV3

fillFromImpl(HGLMModel.HGLMModelOutput) - Method in class hex.schemas.HGLMModelV3.HGLMModelOutputV3

fillFromImpl(IsolationForestModel.IsolationForestParameters) - Method in class hex.schemas.IsolationForestV3.IsolationForestParametersV3

fillFromImpl(IsotonicRegressionModel.IsotonicRegressionOutput) - Method in class hex.schemas.IsotonicRegressionModelV3.IsotonicRegressionModelOutputV3

fillFromImpl(KMeansModel.KMeansOutput) - Method in class hex.schemas.KMeansModelV3.KMeansModelOutputV3

fillFromImpl(ModelSelectionModel.ModelSelectionModelOutput) - Method in class hex.schemas.ModelSelectionModelV3.ModelSelectionModelOutputV3

fillFromImpl(StackedEnsembleModel.StackedEnsembleParameters) - Method in class hex.schemas.StackedEnsembleV99.StackedEnsembleParametersV99

fillFromImpl(UpliftDRFModel.UpliftDRFOutput) - Method in class hex.schemas.UpliftDRFModelV3.UpliftDRFModelOutputV3

fillFromImpl(ModelMetricsAnomaly) - Method in class water.api.ModelMetricsAnomalyV3

fillImpl(IsolationForestModel.IsolationForestParameters) - Method in class hex.schemas.IsolationForestV3.IsolationForestParametersV3

fillImpl(StackedEnsembleModel.StackedEnsembleParameters) - Method in class hex.schemas.StackedEnsembleV99.StackedEnsembleParametersV99

fillInFixedRowValues(DataInfo.Row, double[], HGLMModel.HGLMParameters, int[], int, int, int, DataInfo) - Static method in class hex.hglm.HGLMTask.ComputationEngineTask

fillInput(Chunk[], int, double[], float[], int[]) - Method in class hex.tree.SharedTreeModelWithContributions.ScoreContributionsSortingTask

fillInput(Chunk[], int, double[], float[]) - Method in class hex.tree.SharedTreeModelWithContributions.ScoreContributionsTask

fillInput(Chunk[], int, double[]) - Method in class hex.tree.SharedTreeModelWithContributions.ScoreContributionsWithBackgroundTask

fillModelMetrics(ANOVAGLMModel, GLMModel, Frame) - Static method in class hex.anovaglm.ANOVAGLMUtils

I copied this method from Zuzana Olajcova to add model metrics of the full GLM model as the ANOVAModel model metrics

fillOutput(String[], int[]) - Method in class hex.anovaglm.ANOVAGLMModel

fillRowArray(NewChunk[], int, double[]) - Static method in class hex.gam.GamSplines.ThinPlateRegressionUtils

fillRowData(double[], Chunk[], int, int) - Static method in class hex.gam.GamSplines.ThinPlateDistanceWithKnots

fillRowOneValue(NewChunk[], int, double) - Static method in class hex.gam.GamSplines.ThinPlateRegressionUtils

fillTo(ScoreKeeper) - Method in class hex.tree.isofor.ModelMetricsAnomaly

fillUpCoeffs(double[], double[], TwoDimTable, int) - Static method in class hex.gam.MatrixFrameUtils.GAMModelUtils

fillZTTimesZ(double[][][]) - Static method in class hex.hglm.HGLMUtils

FilteredData(double[][], double[][]) - Constructor for class hex.tree.isoforextended.isolationtree.IsolationTree.FilteredData

filterExpandedColumns(int[]) - Method in class hex.DataInfo

Filter the _adaptedFrame so that it contains only the Vecs referenced by the cols parameter.

filterExpandedColumns(int[]) - Method in class hex.glm.GLM.BetaConstraint

find_maxEx() - Method in class hex.tree.DHistogram

find_maxEx(double, int) - Static method in class hex.tree.DHistogram

find_maxIn() - Method in class hex.tree.DHistogram

find_min() - Method in class hex.tree.DHistogram

findAllPolybasis(List<Integer[]>) - Static method in class hex.gam.GamSplines.ThinPlateRegressionUtils

For each list in onePolyBasis, we still need to find all the permutations for that list.

findAlpha(double[], double[], ComputationState, ConstrainedGLMUtils.LinearConstraints[], ConstrainedGLMUtils.LinearConstraints[], GLM.GLMGradientSolver) - Method in class hex.optimization.OptimizationUtils.ExactLineSearch

Implements the Line Search algorithm in the doc, Algorithm 11.5.

findBestModel(GLM[]) - Static method in class hex.modelselection.ModelSelectionUtils

Given GLM run results of a fixed number of predictors, find the model with the best R2 value.

findCatMinOfMaxZScore(GLMModel, List<Double>) - Static method in class hex.modelselection.ModelSelectionUtils

This method extracts the categorical coefficient z-score (abs(z-value)) by using the following method: 1.

findComboMatch(String[][], int) - Static method in class hex.anovaglm.ANOVAGLMUtils

findEnumInBetaCS(Frame, GLMModel.GLMParameters) - Static method in class hex.glm.GLMUtils

findFullDupPred(DataInfo, List<Integer>, List<String>, List<String>, String[]) - Static method in class hex.modelselection.ModelSelectionUtils

The duplicated columns generated by qr-cholesky is at the level of coefficients.

findGoodCidx(Frame, ArrayList<Integer>, boolean, int, int, int) - Static method in class hex.glrm.GLRM

findIterIndexAcrossFolds(List<Integer>[], int) - Static method in class hex.glm.GLM

This method is used to locate common iteration indices across all folds.

FindMaxIndex(int, double) - Constructor for class hex.util.LinearAlgebraUtils.FindMaxIndex

findMaxNodeId() - Method in class hex.tree.CompressedTree

findMaxTermIndex(Chunk[], int, int) - Method in class hex.glm.DispersionTask.ComputeMaxSumSeriesTsk

findMinZValue(GLMModel, List<String>, List<String>, List<String>) - Static method in class hex.modelselection.ModelSelectionUtils

findNumMinZVal(List<String>, List<Double>, List<String>) - Static method in class hex.modelselection.ModelSelectionUtils

findOnePerm(int, int[], int, ArrayList<int[]>, int[]) - Static method in class hex.gam.GamSplines.ThinPlateRegressionUtils

For a fixed degree specified as totDegree, specified a set of combination of polynomials to achieve the totDegree.

findPermute(int[], List<Integer>, int, List<List<Integer>>) - Static method in class hex.gam.GamSplines.ThinPlateRegressionUtils

findPolyBasis(int, int) - Static method in class hex.gam.GamSplines.ThinPlateRegressionUtils

This method, given number of predictors in the smooth d, number of polynomials in the polynomial basis m, will generate a list of integer array specifying for each predictors the degree that predictor will have.

FindSplits(DHistogram[], Constraints, int, DTree.UndecidedNode) - Constructor for class hex.tree.DTree.DecidedNode.FindSplits

findSynonyms(int, Word2VecSynonymsV3) - Method in class hex.api.Word2VecHandler

findSynonyms(String, int) - Method in class hex.word2vec.Word2VecModel

Find synonyms (i.e.

findtAChunkIndices(Frame, int, int, GLRM.Archetypes) - Static method in class hex.glrm.GLRM

findXChunkIndices(Frame, int, int, GLRM.Archetypes) - Static method in class hex.glrm.GLRM

findZeroCols(double[][]) - Static method in class hex.glm.ComputationState.GramGrad

findZeroCols() - Method in class hex.gram.Gram

fix_dispersion_parameter - Variable in class hex.schemas.GLMV3.GLMParametersV3

fix_tweedie_variance_power - Variable in class hex.schemas.GLMV3.GLMParametersV3

foldChunkId() - Method in class hex.DataInfo

force_load_balance - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

Increase training speed on small datasets by splitting it into many chunks to allow utilization of all cores.

forceStrictlyReproducibleHistograms() - Method in class hex.tree.gbm.GBMModel.GBMParameters

forceStrictlyReproducibleHistograms() - Method in class hex.tree.SharedTreeModel.SharedTreeParameters

Do we need to enable strictly deterministic way of building histograms? Used eg.

form1stOrderDerivatives(int, int, double[]) - Static method in class hex.gam.GamSplines.NBSplinesTypeIDerivative

Method to generate an array of derivatives of NBSplineTypeI.

form2ndDerivCoeffs(int, int, double[]) - Static method in class hex.gam.GamSplines.NBSplinesTypeIDerivative

formConstraintMatrix(ComputationState, List<String>, int[]) - Static method in class hex.glm.ConstrainedGLMUtils

formCPM(Gram, double[], double) - Static method in class hex.modelselection.ModelSelectionUtils

formDerivateProduct(double[][], double[][]) - Static method in class hex.gam.GamSplines.NBSplinesTypeIDerivative

Form product of derivative basis function for index firstIndex, secondIndex like M'i,k(t)*M'j,k(t).

formInfoFrame(Frame, Frame, GLMModel.GLMParameters) - Static method in class hex.glm.TweedieMLDispersionOnly

formXY(double[][], double[], double[]) - Static method in class hex.glm.ComputationState

forwardSolve(double[][], double[]) - Static method in class hex.util.LinearAlgebraUtils

ForwardSolve(DataInfo, double[][]) - Constructor for class hex.util.LinearAlgebraUtils.ForwardSolve

ForwardSolveInPlace(DataInfo, double[][]) - Constructor for class hex.util.LinearAlgebraUtils.ForwardSolveInPlace

forwardStep(List<Integer>, List<Integer>, Set<BitSet>, BitSet, int[][], ModelSelection.SweepModel, boolean) - Method in class hex.modelselection.ModelSelection

Given current predictor subset in currSubsetIndices, this method will add one more predictor to the subset and choose the one that will increase the R2 by the most.

forwardStep(List<Integer>, List<String>, int, List<Integer>, ModelSelectionModel.ModelSelectionParameters, String, int, Model.Parameters.FoldAssignmentScheme, Set<BitSet>) - Static method in class hex.modelselection.ModelSelection

Given a predictor subset with indices stored in currSubsetIndices, one more predictor from the coefNames that was not found in currSubsetIndices was added to the subset to form a new Training frame.

forwardStep(List<Integer>, List<String>, int, List<Integer>, ModelSelectionModel.ModelSelectionParameters, String, int, Model.Parameters.FoldAssignmentScheme) - Static method in class hex.modelselection.ModelSelection

forwardStepR(List<Integer>, List<Integer>, Set<BitSet>, BitSet, int[][], ModelSelection.SweepModel, double, int) - Method in class hex.modelselection.ModelSelection

Given a currSubsetIndices and a predPos, this function will try to look for new predictor that will decrease the error variance compared to bestErrVar.

foundRedundantConstraints(ComputationState, double[][]) - Static method in class hex.glm.ConstrainedGLMUtils

fprop(long, boolean, int) - Method in class hex.deeplearning.Neurons.ExpRectifier

fprop(long, boolean, int) - Method in class hex.deeplearning.Neurons.ExpRectifierDropout

fprop(long, boolean, int) - Method in class hex.deeplearning.Neurons

Forward propagation

fprop(long, boolean, int) - Method in class hex.deeplearning.Neurons.Input

fprop(long, boolean, int) - Method in class hex.deeplearning.Neurons.Linear

fprop(long, boolean, int) - Method in class hex.deeplearning.Neurons.Maxout

fprop(long, boolean, int) - Method in class hex.deeplearning.Neurons.MaxoutDropout

fprop(long, boolean, int) - Method in class hex.deeplearning.Neurons.Rectifier

fprop(long, boolean, int) - Method in class hex.deeplearning.Neurons.RectifierDropout

fprop(long, boolean, int) - Method in class hex.deeplearning.Neurons.Softmax

fprop(long, boolean, int) - Method in class hex.deeplearning.Neurons.Tanh

fprop(long, boolean, int) - Method in class hex.deeplearning.Neurons.TanhDropout

fpropMiniBatch(long, Neurons[], DeepLearningModelInfo, DeepLearningModelInfo, boolean, double[], double[], int) - Static method in class hex.deeplearning.DeepLearningTask

Forward propagation assumption: layer 0 has _a filled with (horizontalized categoricals) double values

frame - Variable in class hex.schemas.DataInfoFrameV3

FrameMap() - Constructor for class hex.tree.SharedTree.FrameMap

FrameMap(SharedTree) - Constructor for class hex.tree.SharedTree.FrameMap

FrameTask<T extends FrameTask<T>> - Class in hex

FrameTask(Key<Job>, DataInfo) - Constructor for class hex.FrameTask

FrameTask(Key<Job>, DataInfo, long, int, boolean) - Constructor for class hex.FrameTask

FrameTask(Key<Job>, DataInfo, long, int, boolean, H2O.H2OCountedCompleter) - Constructor for class hex.FrameTask

FrameTask.ExtractDenseRow - Class in hex

FrameTask2<T extends FrameTask2<T>> - Class in hex

Created by tomasnykodym on 6/1/15.

FrameTask2(H2O.H2OCountedCompleter, DataInfo, Key<Job>) - Constructor for class hex.FrameTask2

FRESH - Static variable in class hex.tree.ScoreBuildHistogram

FriedmanPopescusH - Class in hex.tree

Calculates Friedman and Popescu's H statistics, in order to test for the presence of an interaction between specified variables in h2o gbm and xgb models.

FriedmanPopescusH() - Constructor for class hex.tree.FriedmanPopescusH

frobenius2(double[][]) - Static method in class hex.glrm.GLRM

fromPretrainedModel(Frame) - Static method in class hex.word2vec.Word2Vec

fullCatOffsets() - Method in class hex.DataInfo

fullN() - Method in class hex.DataInfo

Get the fully expanded number of predictor columns.

fullN() - Method in class hex.gram.Gram

fullName() - Method in class hex.adaboost.AdaBoostModel.AdaBoostParameters

fullName() - Method in class hex.aggregator.AggregatorModel.AggregatorParameters

fullName() - Method in class hex.anovaglm.ANOVAGLMModel.ANOVAGLMParameters

fullName() - Method in class hex.coxph.CoxPHModel.CoxPHParameters

fullName() - Method in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

fullName() - Method in class hex.ensemble.StackedEnsembleModel.StackedEnsembleParameters

fullName() - Method in class hex.gam.GAMModel.GAMParameters

fullName() - Method in class hex.generic.GenericModelParameters

fullName() - Method in class hex.glm.GLMModel.GLMParameters

fullName() - Method in class hex.glrm.GLRMModel.GLRMParameters

fullName() - Method in class hex.grep.GrepModel.GrepParameters

fullName() - Method in class hex.hglm.HGLMModel.HGLMParameters

fullName() - Method in class hex.isotonic.IsotonicRegressionModel.IsotonicRegressionParameters

fullName() - Method in class hex.kmeans.KMeansModel.KMeansParameters

fullName() - Method in class hex.modelselection.ModelSelectionModel.ModelSelectionParameters

fullName() - Method in class hex.naivebayes.NaiveBayesModel.NaiveBayesParameters

fullName() - Method in class hex.pca.PCAModel.PCAParameters

fullName() - Method in class hex.psvm.PSVMModel.PSVMParameters

fullName() - Method in class hex.rulefit.RuleFitModel.RuleFitParameters

fullName() - Method in class hex.svd.SVDModel.SVDParameters

fullName() - Method in class hex.tree.drf.DRFModel.DRFParameters

fullName() - Method in class hex.tree.dt.DTModel.DTParameters

fullName() - Method in class hex.tree.gbm.GBMModel.GBMParameters

fullName() - Method in class hex.tree.isofor.IsolationForestModel.IsolationForestParameters

fullName() - Method in class hex.tree.isoforextended.ExtendedIsolationForestModel.ExtendedIsolationForestParameters

fullName() - Method in class hex.tree.uplift.UpliftDRFModel.UpliftDRFParameters

fullName() - Method in class hex.word2vec.Word2VecModel.Word2VecParameters

G

gain(double, double, double, double, double, double, double, double) - Method in class hex.tree.uplift.Divergence

Calculate overall gain as divergence between split gain and node gain.

GAM - Class in hex.gam

GAM(boolean) - Constructor for class hex.gam.GAM

GAM(GAMModel.GAMParameters) - Constructor for class hex.gam.GAM

GAM(GAMModel.GAMParameters, Key<GAMModel>) - Constructor for class hex.gam.GAM

gam_columns - Variable in class hex.schemas.GAMV3.GAMParametersV3

gamma - Variable in class hex.schemas.PSVMV3.PSVMParametersV3

gamma_x - Variable in class hex.schemas.GLRMV3.GLRMParametersV3

gamma_y - Variable in class hex.schemas.GLRMV3.GLRMParametersV3

GAMModel - Class in hex.gam

GAMModel(Key<GAMModel>, GAMModel.GAMParameters, GAMModel.GAMModelOutput) - Constructor for class hex.gam.GAMModel

GAMModel.GAMModelOutput - Class in hex.gam

GAMModel.GAMParameters - Class in hex.gam

GAMModelOutput(GAM, DataInfo) - Constructor for class hex.gam.GAMModel.GAMModelOutput

GAMModelOutputV3() - Constructor for class hex.schemas.GAMModelV3.GAMModelOutputV3

GAMModelUtils - Class in hex.gam.MatrixFrameUtils

GAMModelUtils() - Constructor for class hex.gam.MatrixFrameUtils.GAMModelUtils

GAMModelV3 - Class in hex.schemas

GAMModelV3() - Constructor for class hex.schemas.GAMModelV3

GAMModelV3.GAMModelOutputV3 - Class in hex.schemas

GAMMojoWriter - Class in hex.gam

GAMMojoWriter() - Constructor for class hex.gam.GAMMojoWriter

GAMMojoWriter(GAMModel) - Constructor for class hex.gam.GAMMojoWriter

gamNoCenterCoeffLength(GAMModel.GAMParameters) - Static method in class hex.gam.MatrixFrameUtils.GAMModelUtils

Find the number of gamified column coefficients.

GAMParameters() - Constructor for class hex.gam.GAMModel.GAMParameters

GAMParametersV3() - Constructor for class hex.schemas.GAMV3.GAMParametersV3

GamUtils - Class in hex.gam.MatrixFrameUtils

GamUtils() - Constructor for class hex.gam.MatrixFrameUtils.GamUtils

GamUtils.AllocateType - Enum in hex.gam.MatrixFrameUtils

GAMV3 - Class in hex.schemas

GAMV3() - Constructor for class hex.schemas.GAMV3

GAMV3.GAMParametersV3 - Class in hex.schemas

gaussianVector(int, int, long) - Static method in class hex.tree.isoforextended.isolationtree.IsolationTree

Make a new array initialized to random Gaussian N(0,1) values with the given seed.

GBM - Class in hex.tree.gbm

Gradient Boosted Trees Based on "Elements of Statistical Learning, Second Edition, page 387"

GBM(GBMModel.GBMParameters) - Constructor for class hex.tree.gbm.GBM

GBM(GBMModel.GBMParameters, Key<GBMModel>) - Constructor for class hex.tree.gbm.GBM

GBM(boolean) - Constructor for class hex.tree.gbm.GBM

GBM.DiffMinusMedianDiff - Class in hex.tree.gbm

GBMModel - Class in hex.tree.gbm

GBMModel(Key<GBMModel>, GBMModel.GBMParameters, GBMModel.GBMOutput) - Constructor for class hex.tree.gbm.GBMModel

GBMModel.GBMOutput - Class in hex.tree.gbm

GBMModel.GBMParameters - Class in hex.tree.gbm

GBMModelOutputV3() - Constructor for class hex.schemas.GBMModelV3.GBMModelOutputV3

GBMModelV3 - Class in hex.schemas

GBMModelV3() - Constructor for class hex.schemas.GBMModelV3

GBMModelV3.GBMModelOutputV3 - Class in hex.schemas

GbmMojoWriter - Class in hex.tree.gbm

MOJO support for GBM model.

GbmMojoWriter() - Constructor for class hex.tree.gbm.GbmMojoWriter

GbmMojoWriter(GBMModel) - Constructor for class hex.tree.gbm.GbmMojoWriter

GBMOutput(GBM) - Constructor for class hex.tree.gbm.GBMModel.GBMOutput

GBMParameters() - Constructor for class hex.tree.gbm.GBMModel.GBMParameters

GBMParametersV3() - Constructor for class hex.schemas.GBMV3.GBMParametersV3

GBMV3 - Class in hex.schemas

GBMV3() - Constructor for class hex.schemas.GBMV3

GBMV3.GBMParametersV3 - Class in hex.schemas

gen1OverMLL(double[], double[], double, double) - Method in class hex.glm.RegressionInfluenceDiagnosticsTasks.RegressionInfluenceDiagBinomial

Generate 1.0/(1.0-hjj) for each data row j.

gen_BIndvD(double[]) - Method in class hex.gam.GamSplines.CubicRegressionSplines

gen_penalty_matrix(double[], double[][]) - Method in class hex.gam.GamSplines.CubicRegressionSplines

gen_representation_key(Frame) - Method in class hex.glrm.GLRMModel

gen_syn_data - Variable in class hex.schemas.HGLMV3.HGLMParametersV3

genActiveColsAllClass(int, int, int[], int) - Static method in class hex.glm.ComputationState

genActiveColsIndClass(int, int, int[], int, int) - Method in class hex.glm.ComputationState

genCoefficientMagTable(String[], double[], String[], String) - Method in class hex.gam.GAMModel

genCoefficientMagTableMultinomial(String[], double[][], String[], String) - Method in class hex.gam.GAMModel

genCoefficientTable(String[], double[], double[], String[], String) - Static method in class hex.gam.MatrixFrameUtils.GAMModelUtils

genCoefficientTableMultinomial(String[], double[][], double[][], String[], String) - Static method in class hex.gam.MatrixFrameUtils.GAMModelUtils

genCPMPredNamesIndex(Key, DataInfo, String[], ModelSelectionModel.ModelSelectionParameters) - Static method in class hex.modelselection.ModelSelectionUtils

GenCSSplineGamOneColumn - Class in hex.gam.MatrixFrameUtils

GenCSSplineGamOneColumn(int, int, double[], Frame) - Constructor for class hex.gam.MatrixFrameUtils.GenCSSplineGamOneColumn

genDfBetas(double, double, double[], double[], double) - Method in class hex.glm.RegressionInfluenceDiagnosticsTasks.RegressionInfluenceDiagBinomial

implement operations on and in between equation 5, 6 of the document

genDfbetasNames(GLMModel) - Static method in class hex.glm.GLMUtils

generate2DCoeffTable(String, String, double[][], String[], String[]) - Static method in class hex.schemas.HGLMModelV3

generate_scoring_history - Variable in class hex.schemas.GLMV3.GLMParametersV3

generate_variable_inflation_factors - Variable in class hex.schemas.GLMV3.GLMParametersV3

generateAllErrVar(double[][], Frame, int, List<Integer>, List<Integer>, Set<BitSet>, BitSet, int[][], boolean) - Static method in class hex.modelselection.ModelSelectionUtils

Given the original predictor subset, this function will go into a for loop and choose one predictor out of the remaining predictor set validSubsets and put it into the array allPreds.

generateAllErrVarR(double[][], Frame, double[][], int, List<Integer>, List<Integer>, Set<BitSet>, BitSet, int[][], boolean, int[], ModelSelectionUtils.SweepVector[][]) - Static method in class hex.modelselection.ModelSelectionUtils

Given the original predictor subset, this function will go into a for loop and choose one predictor out of the remaining predictor set validSubsets and put it into the array allPreds.

generateCJInverse(double[][][], double, double[][]) - Static method in class hex.hglm.HGLMUtils

generateCoeffTable(String, String, double[], String[]) - Static method in class hex.schemas.HGLMModelV3

generateGamColNames(int, GAMModel.GAMParameters) - Static method in class hex.gam.MatrixFrameUtils.GamUtils

generateGamColNamesThinPlateKnots(int, GAMModel.GAMParameters, int[][], String) - Static method in class hex.gam.MatrixFrameUtils.GamUtils

generateGLMParameters(Frame[], ModelSelectionModel.ModelSelectionParameters, int, String, Model.Parameters.FoldAssignmentScheme) - Static method in class hex.modelselection.ModelSelectionUtils

generateGLMSS(GLMModel[], GLMModel.GLMParameters.Family) - Static method in class hex.anovaglm.ANOVAGLMUtils

This method is used to generate Model SS for all models built except the full model.

generateIdentityMat(int) - Static method in class hex.util.LinearAlgebraUtils

generateIPC(double[], double, double[], double[], double[]) - Static method in class hex.util.DimensionReductionUtils

This method will calculate the importance of principal components for PCA/GLRM methods.

generateKnotsFromKeys() - Method in class hex.gam.GAM

This method will look at the keys of knots stored in _parms._knot_ids and copy them over to double[][][] array.

generateKnotsOneColumn(Frame, int) - Static method in class hex.gam.MatrixFrameUtils.GamUtils

generateMaxRTrainingFrames(ModelSelectionModel.ModelSelectionParameters, String[], String, List<Integer>, int, List<Integer>, Set<BitSet>) - Static method in class hex.modelselection.ModelSelectionUtils

double

generateModelNames(String[][]) - Static method in class hex.anovaglm.ANOVAGLMUtils

generateNewTmat(double[][]) - Static method in class hex.hglm.HGLMUtils

generateOneCombo(String[], int, List<String[]>) - Static method in class hex.anovaglm.ANOVAGLMUtils

generateOneFrame(int[], Model.Parameters, String[], String) - Static method in class hex.modelselection.ModelSelectionUtils

Given a predictor indices set, this function will generate a training frame containing the predictors with indices in predIndices.

generateOneGAMcols(int, int, double[], double[], double[][], CubicRegressionSplines, double, NewChunk[]) - Method in class hex.gam.MatrixFrameUtils.AddCSGamColumns

generateOneISGAMCols(int, int, double[], ISplines, double, NewChunk[]) - Method in class hex.gam.MatrixFrameUtils.AddISGamColumns

Perform gamification of one column using I-spline basis function described in Section V of doc I.

generateOneMSGAMCols(int, int, double[], double[], MSplines, double, NewChunk[]) - Method in class hex.gam.MatrixFrameUtils.AddMSGamColumns

Perform gamification of one column using I-spline basis function described in Section V of doc I.

generateOrderFreq(Integer[]) - Static method in class hex.gam.GamSplines.ThinPlateRegressionUtils

generateOrthogonalComplement(double[][], double[][], int, long) - Static method in class hex.util.LinearAlgebraUtils

Given an matrix, a QR decomposition is carried out to the matrix as starT = QR.

generatePenalty() - Method in class hex.gam.GamSplines.ThinPlateDistanceWithKnots

generatePredictorCombos(String[], int) - Static method in class hex.anovaglm.ANOVAGLMUtils

In order to calculate Type III SS, we need the individual predictors and their interactions.

generatePredictorNames(String[][], String[][], int[], int[], DataInfo) - Static method in class hex.anovaglm.ANOVAGLMUtils

This method aims to generate the column names of the final transformed frames.

generateQR(double[][]) - Static method in class hex.util.LinearAlgebraUtils

generateRowHeaders(TwoDimTable, TwoDimTable, int, int) - Static method in class hex.glm.GLMUtils

generateStarT(double[][], List<Integer[]>, double[], double[], boolean) - Static method in class hex.gam.GamSplines.ThinPlateRegressionUtils

generateSummary() - Method in class hex.anovaglm.ANOVAGLMModel

The Type III SS calculation, degree of freedom, F-statistics and p-values will be included in the model summary.

generateSummary(Key, int) - Method in class hex.glm.GLMModel

Re-do the TwoDim table generation with updated model.

generateSummary() - Method in class hex.modelselection.ModelSelectionModel.ModelSelectionModelOutput

generateSummary(int) - Method in class hex.modelselection.ModelSelectionModel.ModelSelectionModelOutput

generateTInverse(double[][]) - Static method in class hex.hglm.HGLMUtils

generateTrainingFrames(ModelSelectionModel.ModelSelectionParameters, int, String[], int, String) - Static method in class hex.modelselection.ModelSelectionUtils

GenerateTransformColumns - Class in hex.anovaglm

This class will take two predictors and transform them according to rules specified in Wendy Docs

GenerateTransformColumns(String[][], ANOVAGLMModel.ANOVAGLMParameters, DataInfo, int, String[][]) - Constructor for class hex.anovaglm.GenerateTransformColumns

generateTriDiagMatrix(double[]) - Static method in class hex.util.LinearAlgebraUtils

Generate D matrix as a lower diagonal matrix since it is symmetric and contains only 3 diagonals

generateZTransp(Frame, int) - Static method in class hex.gam.MatrixFrameUtils.GenCSSplineGamOneColumn

Generic - Class in hex.generic

Generic model able to do scoring with any underlying model deserializable into a format known by the GenericModel.

Generic(GenericModelParameters) - Constructor for class hex.generic.Generic

Generic(boolean) - Constructor for class hex.generic.Generic

GenericModel - Class in hex.generic

GenericModel(Key<GenericModel>, GenericModelParameters, GenericModelOutput, MojoModel, Key<Frame>) - Constructor for class hex.generic.GenericModel

Full constructor

GenericModel(Key<GenericModel>, GenericModelParameters, GenericModelOutput, GenModel, Key<Frame>) - Constructor for class hex.generic.GenericModel

GenericModelMojoWriter - Class in hex.generic

GenericModelMojoWriter() - Constructor for class hex.generic.GenericModelMojoWriter

GenericModelMojoWriter(ByteVec) - Constructor for class hex.generic.GenericModelMojoWriter

GenericModelOutput - Class in hex.generic

GenericModelOutput(ModelDescriptor) - Constructor for class hex.generic.GenericModelOutput

GenericModelOutput(ModelDescriptor, ModelAttributes, Table[]) - Constructor for class hex.generic.GenericModelOutput

GenericModelOutputV3() - Constructor for class hex.schemas.GenericModelV3.GenericModelOutputV3

GenericModelParameters - Class in hex.generic

GenericModelParameters() - Constructor for class hex.generic.GenericModelParameters

GenericModelV3 - Class in hex.schemas

GenericModelV3() - Constructor for class hex.schemas.GenericModelV3

GenericModelV3.GenericModelOutputV3 - Class in hex.schemas

GenericParametersV3() - Constructor for class hex.schemas.GenericV3.GenericParametersV3

GenericV3 - Class in hex.schemas

GenericV3() - Constructor for class hex.schemas.GenericV3

GenericV3.GenericParametersV3 - Class in hex.schemas

genGamColumnDim(String[][]) - Method in class hex.gam.GAMMojoWriter

genGLMParameters(GLMModel.GLMParameters, String[], String[]) - Static method in class hex.glm.GLMUtils

genGramCheckDup(Key, DataInfo, ArrayList<Integer>, ModelSelectionModel.ModelSelectionParameters) - Static method in class hex.modelselection.ModelSelectionUtils

genInitBeta() - Method in class hex.glm.GLM

genInitialLambda(Random, ConstrainedGLMUtils.LinearConstraints[], double[]) - Static method in class hex.glm.ConstrainedGLMUtils

The initial value of lambda values really do not matter that much.

genInnerProduct(double[][], double[], double[]) - Static method in class hex.util.LinearAlgebraUtils

genISPenaltyMatrix(double[], int) - Static method in class hex.gam.GamSplines.NBSplinesTypeIDerivative

Generate penalty matrix for I-spline as described in Section VI of doc.

GenISplineGamOneColumn - Class in hex.gam.MatrixFrameUtils

Gamified one gam column at a time using I-spline.

GenISplineGamOneColumn(GAMModel.GAMParameters, double[], int, Frame, int, int) - Constructor for class hex.gam.MatrixFrameUtils.GenISplineGamOneColumn

genKnotsMultiplePreds(Frame, GAMModel.GAMParameters, int) - Static method in class hex.gam.GamSplines.ThinPlateRegressionUtils

Generate knots for thin plate (TP) smoothers.

genMSE1stPred(int[][], double[][], Frame, int[], double[], RecursiveAction[], int, boolean) - Static method in class hex.modelselection.ModelSelectionUtils

This method will calculate the variance variance when only one predictor is considered in allPreds.

genMSE4MorePreds(int[][], double[][], Frame, int[], int, double[], RecursiveAction[], int, boolean) - Static method in class hex.modelselection.ModelSelectionUtils

This method will calculate the error variance value for all predictors in the allPreds.

genMSE4MorePredsR(int[][], double[][], Frame, double[][], int[], double[], RecursiveAction[], int, boolean, ModelSelectionUtils.SweepVector[][], int[]) - Static method in class hex.modelselection.ModelSelectionUtils

Generate the error variance for one predictor subset setting in allPreds.

genMSPenaltyMatrix(double[], int) - Static method in class hex.gam.GamSplines.NBSplinesTypeIDerivative

Generate penalty matrix for M-spline as described in Section III of doc 2.

GenMSplineGamOneColumn - Class in hex.gam.MatrixFrameUtils

GenMSplineGamOneColumn(GAMModel.GAMParameters, double[], int, Frame, int, int) - Constructor for class hex.gam.MatrixFrameUtils.GenMSplineGamOneColumn

Perform gamification on one predictor.

genNewBeta(int, double[], double[]) - Static method in class hex.glm.GLMUtils

genOneDerivative(ConstrainedGLMUtils.LinearConstraints, List<String>) - Static method in class hex.glm.ComputationState

Given a constraint, this method will calculate the first order derivative.

genPolyBasisNames(String[], int[]) - Static method in class hex.gam.MatrixFrameUtils.GamUtils

GenPrediction(double[], GLMModel, DataInfo) - Constructor for class hex.glm.DispersionTask.GenPrediction

genRedundantConstraint(ComputationState, List<Integer>) - Static method in class hex.glm.ConstrainedGLMUtils

genRID() - Method in class hex.glm.GLM.GLMDriver

Generate the regression influence diagnostic for gaussian and binomial families.

genThinPlateNameStart(GAMModel.GAMParameters, int) - Static method in class hex.gam.GamSplines.ThinPlateRegressionUtils

genTrainColGamCols(int, int) - Method in class hex.gam.GAMMojoWriter

get(int, int) - Method in class hex.coxph.Storage.DenseRowMatrix

get(int, int) - Method in interface hex.coxph.Storage.Matrix

get(int) - Method in class hex.DataInfo.Row

get(int, int) - Method in class hex.deeplearning.Storage.DenseColMatrix

get(int, int) - Method in class hex.deeplearning.Storage.DenseRowMatrix

get(int) - Method in class hex.deeplearning.Storage.DenseVector

get(int, int) - Method in interface hex.deeplearning.Storage.Matrix

get(int, int) - Method in class hex.deeplearning.Storage.SparseRowMatrix

get(int, int, int) - Method in interface hex.deeplearning.Storage.Tensor

get(int) - Method in interface hex.deeplearning.Storage.Vector

get(int, int) - Method in class hex.gram.Gram

get_ada_dx_g(int) - Method in class hex.deeplearning.DeepLearningModelInfo

get_avg_activations(int) - Method in class hex.deeplearning.DeepLearningModelInfo

get_biases(int) - Method in class hex.deeplearning.DeepLearningModelInfo

get_biases_ada_dx_g(int) - Method in class hex.deeplearning.DeepLearningModelInfo

get_biases_momenta(int) - Method in class hex.deeplearning.DeepLearningModelInfo

get_global_beta_multinomial() - Method in class hex.glm.GLMModel.GLMOutput

get_params() - Method in class hex.deeplearning.DeepLearningModel

Get the parameters actually used for model building, not the user-given ones (_parms) They might differ since some defaults are filled in, and some invalid combinations are auto-disabled in modifyParams

get_params() - Method in class hex.deeplearning.DeepLearningModelInfo

get_processed_global() - Method in class hex.deeplearning.DeepLearningModelInfo

get_processed_local() - Method in class hex.deeplearning.DeepLearningModelInfo

get_processed_total() - Method in class hex.deeplearning.DeepLearningModelInfo

get_weights(int) - Method in class hex.deeplearning.DeepLearningModelInfo

get_weights_momenta(int) - Method in class hex.deeplearning.DeepLearningModelInfo

getAdditionalParameters() - Method in class hex.schemas.GenericV3.GenericParametersV3

getAlgo() - Method in class hex.ensemble.Metalearners.SimpleMetalearner

getAllAllowedColumnIndices() - Method in class hex.tree.GlobalInteractionConstraints

getAllowedInteractionForIndex(int) - Method in class hex.tree.GlobalInteractionConstraints

getAndValidateCheckpointModel(ModelBuilder<M, P, O>, String[], Value) - Static method in class hex.util.CheckpointUtils

getBeta(double[]) - Method in class hex.glm.GLMModel.Submodel

getBeta() - Method in class hex.hglm.ComputationStateHGLM

getCalibrationFrame() - Method in interface hex.tree.CalibrationHelper.ModelBuilderWithCalibration

getCalibrationFrame() - Method in interface hex.tree.CalibrationHelper.ParamsWithCalibration

getCalibrationFrame() - Method in class hex.tree.SharedTree

getCalibrationFrame() - Method in class hex.tree.SharedTreeModel.SharedTreeParameters

getCalibrationMethod() - Method in interface hex.tree.CalibrationHelper.OutputWithCalibration

getCalibrationMethod() - Method in interface hex.tree.CalibrationHelper.ParamsWithCalibration

getCalibrationMethod() - Method in class hex.tree.SharedTreeModel.SharedTreeParameters

getCat(int, int, int) - Method in class hex.glrm.GLRM.Archetypes

getCatBlock(int) - Method in class hex.glrm.GLRM.Archetypes

getCatCidx(int, int) - Method in class hex.glrm.GLRM.Archetypes

getCategoricalId(int, double) - Method in class hex.DataInfo

getCategoricalId(int, int) - Method in class hex.DataInfo

Get the offset into the expanded categorical

getCategoricalIdFromInteraction(int, int) - Method in class hex.DataInfo

getCategory() - Method in class hex.tree.dt.binning.CategoricalBin

getChildNodeID(Chunk[], int) - Method in class hex.tree.DTree.DecidedNode

GetClassCountsMRTask - Class in hex.tree.dt.mrtasks

MR task for counting classes.

GetClassCountsMRTask(double[][], int) - Constructor for class hex.tree.dt.mrtasks.GetClassCountsMRTask

getCODGradients() - Method in class hex.glm.ComputationState.GramXY

getColumnConstraint(int) - Method in class hex.tree.Constraints

getConstraintFromIndex(ComputationState, Integer) - Static method in class hex.glm.ConstrainedGLMUtils

getCount0() - Method in class hex.tree.dt.binning.AbstractBin

getCriterionValue() - Method in class hex.tree.dt.AbstractSplittingRule

getDataInfoFrame(int, DataInfoFrameV3) - Method in class hex.api.MakeGLMModelHandler

Get the expanded (interactions + offsets) dataset.

getDecisionPath(double[], String[][]) - Method in class hex.tree.CompressedTree

Deprecated.

getDecisionPath(double[], String[][], SharedTreeMojoModel.DecisionPathTracker<T>) - Method in class hex.tree.CompressedTree

getDecisionValue() - Method in class hex.tree.dt.CompressedLeaf

getDepth() - Method in class hex.tree.isoforextended.isolationtree.IsolationTree

getDinfo() - Method in class hex.glm.GLMModel.GLMOutput

getDistributionFamily() - Method in class hex.anovaglm.ANOVAGLMModel.ANOVAGLMParameters

getDistributionFamily() - Method in class hex.ensemble.StackedEnsembleModel.StackedEnsembleParameters

getDistributionFamily() - Method in class hex.gam.GAMModel.GAMParameters

getDistributionFamily() - Method in class hex.glm.GLMModel.GLMParameters

getFastestImplementation() - Static method in enum hex.pca.PCAImplementation

getFeatureBins(int) - Method in class hex.tree.dt.binning.Histogram

Get list of feature bins (copy) - for testing.

getFeatureIndex() - Method in class hex.rulefit.Condition

getFeatureIndex() - Method in class hex.tree.dt.AbstractSplittingRule

getFeatureInteractions(int, int, int) - Method in class hex.tree.gbm.GBMModel

getFeatureInteractionsTable(int, int, int) - Method in class hex.tree.gbm.GBMModel

getFeatureLimits(int) - Method in class hex.tree.dt.DataFeaturesLimits

getFeaturesLimitsForConditions(Frame, DataFeaturesLimits) - Static method in class hex.tree.dt.binning.Histogram

Computes features limits considering known condition limits of ancestors.

getFixedCofficientNames() - Method in class hex.hglm.ComputationStateHGLM

getFriedmanPopescusH(Frame, String[]) - Method in class hex.tree.gbm.GBMModel

getGenModelEncoding() - Method in class hex.deeplearning.DeepLearningModel

getGenModelEncoding() - Method in class hex.tree.SharedTreeModel

getGlobalSplitPointsKey(int) - Method in class hex.tree.SharedTree.Driver

getGlobalSplitPointsKeys() - Method in class hex.tree.SharedTree.Driver

getGradient(double[], ComputationState) - Method in class hex.glm.GLM.GLMGradientSolver

This method calculates the gradient for constrained GLM without taking into account the contribution of the constraints in this case.

getGradient(double[]) - Method in class hex.glm.GLM.GLMGradientSolver

getGradient(double[]) - Method in class hex.glm.GLM.ProximalGradientSolver

getGradient(double[]) - Method in interface hex.optimization.OptimizationUtils.GradientSolver

Evaluate ginfo at solution beta.

getGram() - Method in class hex.glm.GLMTask.GLMIterationTask

getGroupColumnNames() - Method in class hex.hglm.ComputationStateHGLM

getHeight() - Method in class hex.tree.isoforextended.isolationtree.AbstractCompressedNode

getHeight() - Method in class hex.tree.isoforextended.isolationtree.IsolationTree.Node

getId() - Method in enum hex.tree.CalibrationHelper.CalibrationMethod

getInformationTableNumRows() - Method in class hex.tree.SharedTreeModel.SharedTreeOutput

getInitialFeaturesLimits(Frame) - Static method in class hex.tree.dt.DT

Compute initial features limits.

getInitialValue() - Method in class hex.tree.SharedTree

Compute the inital value for a given distribution

getInstance() - Static method in class hex.deeplearning.MurmurHash

getInteractionOffset(Chunk[], int, int) - Method in class hex.DataInfo

getInv() - Method in class hex.gram.Gram.Cholesky

getInvDiag() - Method in class hex.gram.Gram.Cholesky

getIsolatedPoints() - Method in class hex.tree.isoforextended.isolationtree.IsolationTree

getL() - Method in class hex.gram.Gram.Cholesky

getL() - Method in class hex.gram.Gram.InPlaceCholesky

getLambdaNull() - Method in class hex.glm.ComputationState

getLeaves() - Method in class hex.tree.isoforextended.isolationtree.IsolationTree

getLeft() - Method in class hex.tree.isoforextended.isolationtree.IsolationTree.FilteredData

getLevel2UnitIndex() - Method in class hex.hglm.ComputationStateHGLM

getLinearNames(int, String[]) - Static method in class hex.rulefit.RuleFitUtils

getListOfRules() - Method in class hex.tree.dt.CompressedDT

getMask() - Method in class hex.tree.dt.CategoricalSplittingRule

getMatrixInString(double[][]) - Static method in class hex.util.LinearAlgebraUtils

getMetricsBuilder() - Method in class hex.tree.dt.mrtasks.ScoreDTTask

getMiniBatchSize() - Method in class hex.deeplearning.DeepLearningTask

getMiniBatchSize() - Method in class hex.FrameTask

Note: If this is overridden, then applyMiniBatch must be overridden as well to perform the model/weight mini-batch update

getModelBuilder() - Method in interface hex.tree.CalibrationHelper.ModelBuilderWithCalibration

getModelBuilder() - Method in class hex.tree.SharedTree

getModelCategory() - Method in class hex.aggregator.AggregatorModel.AggregatorOutput

getModelCategory() - Method in class hex.anovaglm.ANOVAGLMModel.ANOVAGLMModelOutput

getModelCategory() - Method in class hex.coxph.CoxPHModel.CoxPHOutput

getModelCategory() - Method in class hex.deeplearning.DeepLearningModel.DeepLearningModelOutput

getModelCategory() - Method in class hex.gam.GAMModel.GAMModelOutput

getModelCategory() - Method in class hex.generic.GenericModelOutput

getModelCategory() - Method in class hex.glm.GLMModel.GLMOutput

getModelCategory() - Method in class hex.glrm.GLRMModel.GLRMOutput

getModelCategory() - Method in class hex.grep.GrepModel.GrepOutput

getModelCategory() - Method in class hex.hglm.HGLMModel.HGLMModelOutput

getModelCategory() - Method in class hex.isotonic.IsotonicRegressionModel.IsotonicRegressionOutput

getModelCategory() - Method in class hex.modelselection.ModelSelectionModel.ModelSelectionModelOutput

getModelCategory() - Method in class hex.pca.PCAModel.PCAOutput

getModelCategory() - Method in class hex.psvm.PSVMModel.PSVMModelOutput

getModelCategory() - Method in class hex.svd.SVDModel.SVDOutput

getModelCategory() - Method in interface hex.tree.CalibrationHelper.OutputWithCalibration

getModelCategory() - Method in class hex.tree.isofor.IsolationForestModel.IsolationForestOutput

getModelCategory() - Method in class hex.tree.isoforextended.ExtendedIsolationForestModel.ExtendedIsolationForestOutput

getModelCategory() - Method in class hex.tree.uplift.UpliftDRFModel.UpliftDRFOutput

getModelCategory() - Method in class hex.word2vec.Word2VecModel.Word2VecOutput

getMojo() - Method in class hex.coxph.CoxPHModel

getMojo() - Method in class hex.deeplearning.DeepLearningModel

getMojo() - Method in class hex.ensemble.StackedEnsembleModel

getMojo() - Method in class hex.gam.GAMModel

getMojo() - Method in class hex.generic.GenericModel

getMojo() - Method in class hex.glm.GLMModel

getMojo() - Method in class hex.glrm.GLRMGenX

getMojo() - Method in class hex.glrm.GLRMModel

getMojo() - Method in class hex.isotonic.IsotonicRegressionModel

getMojo() - Method in class hex.kmeans.KMeansModel

getMojo() - Method in class hex.pca.PCAModel

getMojo() - Method in class hex.rulefit.RuleFitModel

getMojo() - Method in class hex.tree.drf.DRFModel

getMojo() - Method in class hex.tree.gbm.GBMModel

getMojo() - Method in class hex.tree.isofor.IsolationForestModel

getMojo() - Method in class hex.tree.isoforextended.ExtendedIsolationForestModel

getMojo() - Method in class hex.tree.uplift.UpliftDRFModel

getMojo() - Method in class hex.word2vec.Word2VecModel

getMostImportantFeatures(int) - Method in class hex.tree.SharedTreeModel

getMultinomialLikelihood(double[]) - Method in class hex.glm.GLM.GLMGradientSolver

getN() - Method in class hex.tree.isoforextended.isolationtree.CompressedNode

getN() - Method in class hex.tree.isoforextended.isolationtree.IsolationTree.Node

getName() - Method in class hex.api.RegisterAlgos

getName() - Method in interface hex.ensemble.MetalearnerProvider

getNodes() - Method in class hex.tree.dt.CompressedDT

getNodes() - Method in class hex.tree.isoforextended.isolationtree.CompressedIsolationTree

getNonPredictors() - Method in class hex.ensemble.StackedEnsembleModel.StackedEnsembleParameters

getNormBeta() - Method in class hex.glm.GLMModel.GLMOutput

getNormBeta() - Method in class hex.modelselection.ModelSelectionModel.ModelSelectionModelOutput

getNormBetaMultinomial() - Method in class hex.glm.GLMModel.GLMOutput

getNormBetaMultinomial(int) - Method in class hex.glm.GLMModel.GLMOutput

getNormBetaMultinomial(int, boolean) - Method in class hex.glm.GLMModel.GLMOutput

getNotIsolatedPoints() - Method in class hex.tree.isoforextended.isolationtree.IsolationTree

getNTrees() - Method in class hex.tree.SharedTreeModel.SharedTreeOutput

getNTrees() - Method in class hex.tree.SharedTreeModel.SharedTreeParameters

getNum(int, int) - Method in class hex.glrm.GLRM.Archetypes

getNumCatTreshold() - Method in class hex.rulefit.Condition

getNumCidx(int) - Method in class hex.glrm.GLRM.Archetypes

getNumFixedCoeffs() - Method in class hex.hglm.ComputationStateHGLM

getNumLevel2Units() - Method in class hex.hglm.ComputationStateHGLM

getNumRandomCoeffs() - Method in class hex.hglm.ComputationStateHGLM

getNumRows() - Method in class hex.tree.isoforextended.isolationtree.CompressedLeaf

getNumRows() - Method in class hex.tree.isoforextended.isolationtree.IsolationTree.Node

getNumTreshold() - Method in class hex.rulefit.Condition

getObj() - Method in interface hex.optimization.OptimizationUtils.LineSearchSolver

getObj() - Method in class hex.optimization.OptimizationUtils.MoreThuente

getObj() - Method in class hex.optimization.OptimizationUtils.SimpleBacktrackingLS

getObjective(double[]) - Method in class hex.glm.GLM.GLMGradientSolver

getObjective(double[]) - Method in class hex.glm.GLM.ProximalGradientSolver

getObjective(double[]) - Method in interface hex.optimization.OptimizationUtils.GradientSolver

getOffsetVec() - Method in class hex.DataInfo

getOperator() - Method in class hex.rulefit.Condition

getOutputVec(int) - Method in class hex.DataInfo

getP() - Method in class hex.tree.isoforextended.isolationtree.CompressedNode

getP() - Method in class hex.tree.isoforextended.isolationtree.IsolationTree.Node

getParams() - Method in interface hex.tree.CalibrationHelper.ParamsWithCalibration

getParams() - Method in class hex.tree.SharedTreeModel.SharedTreeParameters

getParams() - Method in class hex.word2vec.Word2VecModel.Word2VecModelInfo

getPathNames(int, int, String[]) - Static method in class hex.rulefit.RuleFitUtils

getPojoInterfaces() - Method in class hex.kmeans.KMeansModel

getPrediction(double[]) - Method in class hex.tree.Score.ScoreExtension

Get prediction from per class-probabilities or algo-specific data

getPrincipalComponents() - Method in class hex.pca.jama.PCAJama

getPrincipalComponents() - Method in class hex.pca.mtj.PCA_MTJ_EVD_DenseMatrix

getPrincipalComponents() - Method in class hex.pca.mtj.PCA_MTJ_EVD_SymmMatrix

getPrincipalComponents() - Method in class hex.pca.mtj.PCA_MTJ_SVD_DenseMatrix

getPrincipalComponents() - Method in interface hex.pca.PCAInterface

getProbabilities() - Method in class hex.tree.dt.CompressedLeaf

getProblemType() - Method in class hex.tree.isofor.IsolationForest

getProblemType() - Method in class hex.tree.SharedTree

getRandomCoefficientNames() - Method in class hex.hglm.ComputationStateHGLM

getRawVals() - Method in class hex.tree.DHistogram

getRegularizationPath() - Method in class hex.glm.GLMModel

getResponseComplements(SharedTreeModel<?, ?, ?>) - Method in class hex.tree.Score.ScoreExtension

Return indices of columns that need to be extracted from Frame chunks in addition to response

getResponseLevelIndex(String, SharedTreeModel.SharedTreeOutput) - Static method in class hex.tree.TreeUtils

getRIDFrame() - Method in class hex.glm.GLMModel

getRight() - Method in class hex.tree.isoforextended.isolationtree.IsolationTree.FilteredData

getRuleByVarName(String) - Method in class hex.rulefit.RuleEnsemble

getRuleImportanceTable() - Method in class hex.rulefit.RuleFitModel

getScoreContributionsSoringTask(SharedTreeModel, Model.Contributions.ContributionsOptions) - Method in class hex.tree.drf.DRFModel

getScoreContributionsSoringTask(SharedTreeModel, Model.Contributions.ContributionsOptions) - Method in class hex.tree.gbm.GBMModel

getScoreContributionsSoringTask(SharedTreeModel, Model.Contributions.ContributionsOptions) - Method in class hex.tree.SharedTreeModelWithContributions

getScoreContributionsTask(SharedTreeModel) - Method in class hex.tree.drf.DRFModel

getScoreContributionsTask(SharedTreeModel) - Method in class hex.tree.gbm.GBMModel

getScoreContributionsTask(SharedTreeModel) - Method in class hex.tree.SharedTreeModelWithContributions

getScoreContributionsWithBackgroundTask(SharedTreeModel, Frame, Frame, boolean, int[], Model.Contributions.ContributionsOptions) - Method in class hex.tree.drf.DRFModel

getScoreContributionsWithBackgroundTask(SharedTreeModel, Frame, Frame, boolean, int[], Model.Contributions.ContributionsOptions) - Method in class hex.tree.gbm.GBMModel

getScoreContributionsWithBackgroundTask(SharedTreeModel, Frame, Frame, boolean, int[], Model.Contributions.ContributionsOptions) - Method in class hex.tree.SharedTreeModelWithContributions

getScoringInfo() - Method in class hex.glm.GLMModel

getSearchDirection(double[], double[]) - Method in class hex.optimization.L_BFGS.History

getSeed() - Method in class hex.tree.CompressedTree

getSharedTreeSubgraph(int, int) - Method in class hex.tree.SharedTreeModel

Converts a given tree of the ensemble to a user-understandable representation.

getSplitPrediction() - Method in class hex.tree.DTree.LeafNode

getSplittingRule() - Method in class hex.tree.dt.CompressedNode

getSubmodel(double) - Method in class hex.glm.GLMModel.GLMOutput

getSubmodel(int) - Method in class hex.glm.GLMModel.GLMOutput

getSubModels() - Method in class hex.ensemble.StackedEnsembleMojoWriter

getSubModels() - Method in class hex.rulefit.RuleFitMojoWriter

getT() - Method in class hex.hglm.ComputationStateHGLM

getTauEVarE10() - Method in class hex.hglm.ComputationStateHGLM

getTauUVar() - Method in class hex.hglm.ComputationStateHGLM

getThreshold() - Method in class hex.tree.dt.NumericSplittingRule

getToEigenVec() - Method in class hex.aggregator.Aggregator

getToEigenVec() - Method in class hex.aggregator.AggregatorModel

getToEigenVec() - Method in class hex.deeplearning.DeepLearning

getToEigenVec() - Method in class hex.deeplearning.DeepLearningModel

getToEigenVec() - Method in class hex.kmeans.KMeans

getToEigenVec() - Method in class hex.kmeans.KMeansModel

getToEigenVec() - Method in class hex.rulefit.RuleFitModel

getToEigenVec() - Method in class hex.tree.SharedTree

getToEigenVec() - Method in class hex.tree.SharedTreeModel

getTransformedEigenvectors(DataInfo, double[][]) - Static method in class hex.util.DimensionReductionUtils

This function will tranform the eigenvectors calculated for a matrix T(A) to the ones calculated for matrix A.

getTree(int, TreeV3) - Method in class hex.tree.TreeHandler

getType() - Method in class hex.rulefit.Condition

getUbeta() - Method in class hex.hglm.ComputationStateHGLM

getVariableImportances() - Method in class hex.deeplearning.DeepLearningModel.DeepLearningModelOutput

getVariableImportances() - Method in class hex.glm.GLMModel.GLMOutput

getVariableImportances() - Method in class hex.tree.SharedTreeModel.SharedTreeOutput

getVariableInflationFactors() - Method in class hex.glm.GLMModel.GLMOutput

getVariances() - Method in class hex.pca.jama.PCAJama

getVariances() - Method in class hex.pca.mtj.PCA_MTJ_EVD_DenseMatrix

getVariances() - Method in class hex.pca.mtj.PCA_MTJ_EVD_SymmMatrix

getVariances() - Method in class hex.pca.mtj.PCA_MTJ_SVD_DenseMatrix

getVariances() - Method in interface hex.pca.PCAInterface

getVIFAndNames() - Method in class hex.glm.GLMModel.GLMOutput

getVIFPredictorNames() - Method in class hex.glm.GLMModel.GLMOutput

getWeightsVec() - Method in class hex.DataInfo

getX() - Method in interface hex.optimization.OptimizationUtils.LineSearchSolver

getX() - Method in class hex.optimization.OptimizationUtils.MoreThuente

getX() - Method in class hex.optimization.OptimizationUtils.SimpleBacktrackingLS

getXChunk(Frame, int, Chunk[]) - Static method in class hex.glrm.GLRM

getXX() - Method in class hex.gram.Gram

getXX(boolean, boolean) - Method in class hex.gram.Gram

getXX(double[][]) - Method in class hex.gram.Gram

getXX(double[][], boolean, boolean) - Method in class hex.gram.Gram

getXXCPM(double[][], boolean, boolean) - Method in class hex.gram.Gram

This method will copy the xx matrix into a matrix xalloc which is of bigger size than the actual xx by 1 in both row and column.

getXY() - Method in class hex.glm.GLMTask.GLMIterationTask

getY(boolean) - Method in class hex.glrm.GLRM.Archetypes

getYY() - Method in class hex.glm.GLMTask.GLMIterationTask

getZeroSplits() - Method in class hex.tree.isoforextended.isolationtree.IsolationTree

getZValues() - Method in class hex.glm.GLMModel.GLMOutput

getZValues(double[]) - Method in class hex.glm.GLMModel.Submodel

ginfo() - Method in class hex.glm.ComputationState

ginfo - Variable in class hex.optimization.L_BFGS.Result

ginfo() - Method in interface hex.optimization.OptimizationUtils.LineSearchSolver

ginfo() - Method in class hex.optimization.OptimizationUtils.MoreThuente

ginfo() - Method in class hex.optimization.OptimizationUtils.SimpleBacktrackingLS

ginfoMultinomial(int) - Method in class hex.glm.ComputationState

ginfoMultinomialRCC(int) - Method in class hex.glm.ComputationState

ginfoNull() - Method in class hex.glm.ComputationState

GLM - Class in hex.glm

Created by tomasnykodym on 8/27/14.

GLM(boolean) - Constructor for class hex.glm.GLM

GLM(GLMModel.GLMParameters) - Constructor for class hex.glm.GLM

GLM(GLMModel.GLMParameters, double[][][], String[][]) - Constructor for class hex.glm.GLM

This constructor is only called by GAM when it is trying to build a GAM model using GLM.

GLM(GLMModel.GLMParameters, Key) - Constructor for class hex.glm.GLM

GLM.BetaConstraint - Class in hex.glm

GLM.BetaInfo - Class in hex.glm

GLM.GLMDriver - Class in hex.glm

Main loop of the glm algo.

GLM.GLMGradientInfo - Class in hex.glm

GLM.GLMGradientSolver - Class in hex.glm

Gradient and line search computation for L_BFGS and also L_BFGS solver wrapper (for ADMM)

GLM.GramSolver - Class in hex.glm

Created by tomasnykodym on 3/30/15.

GLM.PlugValuesImputer - Class in hex.glm

GLM.ProximalGradientInfo - Class in hex.glm

GLM.ProximalGradientSolver - Class in hex.glm

Simple wrapper around ginfo computation, adding proximal penalty

GLMCoordinateDescentTaskSeqIntercept(double[], DataInfo) - Constructor for class hex.glm.GLMTask.GLMCoordinateDescentTaskSeqIntercept

GLMCoordinateDescentTaskSeqNaive(boolean, boolean, int, double[], double[], int[], int[], double[], double[], double[], double[], boolean) - Constructor for class hex.glm.GLMTask.GLMCoordinateDescentTaskSeqNaive

GLMDriver() - Constructor for class hex.glm.GLM.GLMDriver

GLMGaussianGradientTask(Key, DataInfo, GLMModel.GLMParameters, double, double[]) - Constructor for class hex.glm.GLMTask.GLMGaussianGradientTask

GLMGaussianGradientTask(Key, DataInfo, GLMModel.GLMParameters, double, double[], double[][][], int[][]) - Constructor for class hex.glm.GLMTask.GLMGaussianGradientTask

GLMGenerateWeightsTask(Key, DataInfo, GLMModel.GLMParameters, double[]) - Constructor for class hex.glm.GLMTask.GLMGenerateWeightsTask

GLMGradientInfo(double, double, double[]) - Constructor for class hex.glm.GLM.GLMGradientInfo

GLMGradientSolver(Job, GLMModel.GLMParameters, DataInfo, double, GLM.BetaConstraint, GLM.BetaInfo) - Constructor for class hex.glm.GLM.GLMGradientSolver

GLMGradientSolver(Job, GLMModel.GLMParameters, DataInfo, double, GLM.BetaConstraint, GLM.BetaInfo, double[][][], int[][]) - Constructor for class hex.glm.GLM.GLMGradientSolver

GLMIterationTask(Key, DataInfo, GLMModel.GLMWeightsFun, double[]) - Constructor for class hex.glm.GLMTask.GLMIterationTask

GLMIterationTask(Key, DataInfo, GLMModel.GLMWeightsFun, double[], int) - Constructor for class hex.glm.GLMTask.GLMIterationTask

GLMIterationTaskMultinomial(DataInfo, Key, double[], int) - Constructor for class hex.glm.GLMTask.GLMIterationTaskMultinomial

GLMMetricBuilder - Class in hex.glm

Class for GLMValidation.

GLMMetricBuilder(String[], double[], GLMModel.GLMWeightsFun, int, boolean, boolean, MultinomialAucType) - Constructor for class hex.glm.GLMMetricBuilder

GLMModel - Class in hex.glm

Created by tomasnykodym on 8/27/14.

GLMModel(Key, GLMModel.GLMParameters, GLM, double[], double, double, long) - Constructor for class hex.glm.GLMModel

GLMModel.GLMOutput - Class in hex.glm

GLMModel.GLMParameters - Class in hex.glm

GLMModel.GLMParameters.Constraints - Enum in hex.glm

GLMModel.GLMParameters.DispersionMethod - Enum in hex.glm

GLMModel.GLMParameters.Family - Enum in hex.glm

GLMModel.GLMParameters.GLMType - Enum in hex.glm

GLMModel.GLMParameters.Influence - Enum in hex.glm

GLMModel.GLMParameters.Link - Enum in hex.glm

GLMModel.GLMParameters.MissingValuesHandling - Enum in hex.glm

GLMModel.GLMParameters.Solver - Enum in hex.glm

GLMModel.GLMWeights - Class in hex.glm

GLMModel.GLMWeightsFun - Class in hex.glm

GLMModel.RegularizationPath - Class in hex.glm

GLMModel.Submodel - Class in hex.glm

GLMModelOutputV3() - Constructor for class hex.schemas.GLMModelV3.GLMModelOutputV3

GLMModelV3 - Class in hex.schemas

GLMModelV3() - Constructor for class hex.schemas.GLMModelV3

GLMModelV3.GLMModelOutputV3 - Class in hex.schemas

GLMMojoWriter - Class in hex.glm

GLMMojoWriter() - Constructor for class hex.glm.GLMMojoWriter

GLMMojoWriter(GLMModel) - Constructor for class hex.glm.GLMMojoWriter

GLMMultinomialGradientBaseTask(Job, DataInfo, double, double[][], double) - Constructor for class hex.glm.GLMTask.GLMMultinomialGradientBaseTask

GLMMultinomialGradientBaseTask(Job, DataInfo, double, double[][], GLMModel.GLMParameters) - Constructor for class hex.glm.GLMTask.GLMMultinomialGradientBaseTask

GLMMultinomialGradientBaseTask(Job, DataInfo, double, double[][], GLMModel.GLMParameters, double[][][], int[][]) - Constructor for class hex.glm.GLMTask.GLMMultinomialGradientBaseTask

GLMMultinomialGradientTask(Job, DataInfo, double, double[][], double) - Constructor for class hex.glm.GLMTask.GLMMultinomialGradientTask

GLMMultinomialGradientTask(Job, DataInfo, double, double[][], GLMModel.GLMParameters) - Constructor for class hex.glm.GLMTask.GLMMultinomialGradientTask

GLMMultinomialGradientTask(Job, DataInfo, double, double[][], GLMModel.GLMParameters, double[][][], int[][]) - Constructor for class hex.glm.GLMTask.GLMMultinomialGradientTask

GLMMultinomialUpdate(DataInfo, Key, double[], int) - Constructor for class hex.glm.GLMTask.GLMMultinomialUpdate

GLMMultinomialWLSTask(H2O.H2OCountedCompleter, DataInfo, Key, GLMModel.GLMWeightsFun, double[]) - Constructor for class hex.glm.GLMTask.GLMMultinomialWLSTask

GLMOutput(DataInfo, String[], String[], String[][], String[], double[], boolean, boolean, boolean) - Constructor for class hex.glm.GLMModel.GLMOutput

GLMOutput() - Constructor for class hex.glm.GLMModel.GLMOutput

GLMOutput(GLM) - Constructor for class hex.glm.GLMModel.GLMOutput

GLMParameters() - Constructor for class hex.glm.GLMModel.GLMParameters

GLMParameters(GLMModel.GLMParameters.Family) - Constructor for class hex.glm.GLMModel.GLMParameters

GLMParameters(GLMModel.GLMParameters.Family, GLMModel.GLMParameters.Link) - Constructor for class hex.glm.GLMModel.GLMParameters

GLMParameters(GLMModel.GLMParameters.Family, GLMModel.GLMParameters.Link, double[], double[], double, double) - Constructor for class hex.glm.GLMModel.GLMParameters

GLMParameters(GLMModel.GLMParameters.Family, GLMModel.GLMParameters.Link, double[], double[], double, double, String[]) - Constructor for class hex.glm.GLMModel.GLMParameters

GLMParameters(GLMModel.GLMParameters.Family, GLMModel.GLMParameters.Link, double[], double[], double, double, String[], double) - Constructor for class hex.glm.GLMModel.GLMParameters

GLMParameters(GLMModel.GLMParameters.Family, GLMModel.GLMParameters.Link, double[], double[], double, double, String[], double, double) - Constructor for class hex.glm.GLMModel.GLMParameters

GLMParametersV3() - Constructor for class hex.schemas.GLMV3.GLMParametersV3

GLMRegularizationPathV3 - Class in hex.schemas

GLMRegularizationPathV3() - Constructor for class hex.schemas.GLMRegularizationPathV3

GLMScore - Class in hex.glm

Created by tomas on 3/15/16.

GLMScore(Job, GLMModel, DataInfo, String[], boolean, boolean, CFuncRef) - Constructor for class hex.glm.GLMScore

GLMScoringInfo - Class in hex.glm

GLMScoringInfo() - Constructor for class hex.glm.GLMScoringInfo

GLMSubsetGinfo(GLM.GLMGradientInfo, int, int, int[]) - Constructor for class hex.glm.ComputationState.GLMSubsetGinfo

GLMTask - Class in hex.glm

All GLM related distributed tasks: YMUTask - computes response means on actual datasets (if some rows are ignored - e.g ignoring rows with NA and/or doing cross-validation) GLMGradientTask - computes gradient at given Beta, used by L-BFGS, for KKT condition check GLMLineSearchTask - computes residual deviance(s) at given beta(s), used by line search (both L-BFGS and IRLSM) GLMIterationTask - used by IRLSM to compute Gram matrix and response t(X) W X, t(X)Wz

GLMTask() - Constructor for class hex.glm.GLMTask

GLMTask.ComputeDiTriGammaTsk - Class in hex.glm

This function will assist in the estimation of dispersion factors using maximum likelihood

GLMTask.ComputeGammaMLSETsk - Class in hex.glm

This function will assist in the estimation of dispersion factors using maximum likelihood

GLMTask.ComputeSEorDEVIANCETsk - Class in hex.glm

GLMTask.GLMCoordinateDescentTaskSeqIntercept - Class in hex.glm

GLMTask.GLMCoordinateDescentTaskSeqNaive - Class in hex.glm

GLMTask.GLMGaussianGradientTask - Class in hex.glm

GLMTask.GLMGenerateWeightsTask - Class in hex.glm

GLMTask.GLMIterationTask - Class in hex.glm

One iteration of glm, computes weighted gram matrix and t(x)*y vector and t(y)*y scalar.

GLMTask.GLMIterationTaskMultinomial - Class in hex.glm

GLMTask.GLMMultinomialGradientBaseTask - Class in hex.glm

GLMTask.GLMMultinomialGradientTask - Class in hex.glm

GLMTask.GLMMultinomialUpdate - Class in hex.glm

GLMTask.GLMMultinomialWLSTask - Class in hex.glm

GLMTask.GLMWLSTask - Class in hex.glm

GLMTask.LSTask - Class in hex.glm

Task to compute t(X) %*% W %*% X and t(X) %*% W %*% y

GLMTask.YMUTask - Class in hex.glm

GLMUtils - Class in hex.glm

GLMUtils() - Constructor for class hex.glm.GLMUtils

GLMV3 - Class in hex.schemas

Created by tomasnykodym on 8/29/14.

GLMV3() - Constructor for class hex.schemas.GLMV3

GLMV3.GLMParametersV3 - Class in hex.schemas

GLMWeights() - Constructor for class hex.glm.GLMModel.GLMWeights

GLMWeightsFun(GLMModel.GLMParameters) - Constructor for class hex.glm.GLMModel.GLMWeightsFun

GLMWeightsFun(GLMModel.GLMParameters.Family, GLMModel.GLMParameters.Link, double, double, double, double, boolean) - Constructor for class hex.glm.GLMModel.GLMWeightsFun

GLMWLSTask(H2O.H2OCountedCompleter, DataInfo, Key, GLMModel.GLMWeightsFun, double[]) - Constructor for class hex.glm.GLMTask.GLMWLSTask

GlobalInteractionConstraints - Class in hex.tree

Class to process global interaction constraints information and use this information for make a split decision in a tree.

GlobalInteractionConstraints(String[][], String[]) - Constructor for class hex.tree.GlobalInteractionConstraints

GLRM - Class in hex.glrm

Generalized Low Rank Models This is an algorithm for dimensionality reduction of a dataset.

GLRM(GLRMModel.GLRMParameters) - Constructor for class hex.glrm.GLRM

GLRM(GLRMModel.GLRMParameters, Job<GLRMModel>) - Constructor for class hex.glrm.GLRM

GLRM(boolean) - Constructor for class hex.glrm.GLRM

GLRM.Archetypes - Class in hex.glrm

GLRM.updateXVecs - Class in hex.glrm

GLRMGenX - Class in hex.glrm

GLRMGenX will generate the coefficients (X matrix) of a GLRM model given the archetype for a dataframe.

GLRMGenX(GLRMModel, int) - Constructor for class hex.glrm.GLRMGenX

GLRMModel - Class in hex.glrm

GLRM (Generalized Low Rank Model).

GLRMModel(Key<GLRMModel>, GLRMModel.GLRMParameters, GLRMModel.GLRMOutput) - Constructor for class hex.glrm.GLRMModel

GLRMModel.GLRMOutput - Class in hex.glrm

GLRMModel.GLRMParameters - Class in hex.glrm

GlrmModelMetricsBuilder(int, int[]) - Constructor for class hex.glrm.ModelMetricsGLRM.GlrmModelMetricsBuilder

GlrmModelMetricsBuilder(int, int[], boolean) - Constructor for class hex.glrm.ModelMetricsGLRM.GlrmModelMetricsBuilder

GLRMModelOutputV3() - Constructor for class hex.schemas.GLRMModelV3.GLRMModelOutputV3

GLRMModelV3 - Class in hex.schemas

GLRMModelV3() - Constructor for class hex.schemas.GLRMModelV3

GLRMModelV3.GLRMModelOutputV3 - Class in hex.schemas

GlrmMojoWriter - Class in hex.glrm

MOJO serializer for GLRM model.

GlrmMojoWriter() - Constructor for class hex.glrm.GlrmMojoWriter

GlrmMojoWriter(GLRMModel) - Constructor for class hex.glrm.GlrmMojoWriter

GLRMOutput(GLRM) - Constructor for class hex.glrm.GLRMModel.GLRMOutput

GLRMParameters() - Constructor for class hex.glrm.GLRMModel.GLRMParameters

GLRMParametersV3() - Constructor for class hex.schemas.GLRMV3.GLRMParametersV3

GLRMV3 - Class in hex.schemas

GLRMV3() - Constructor for class hex.schemas.GLRMV3

GLRMV3.GLRMParametersV3 - Class in hex.schemas

go(int, boolean) - Method in class hex.tree.SharedTreeModel.BufStringDecisionPathTracker

grabCatIndexVal(DataInfo.Row, int, int, DataInfo) - Static method in class hex.hglm.HGLMTask.ComputationEngineTask

grabInitValuesFromFrame(Key, double[][]) - Static method in class hex.hglm.HGLMUtils

grabRedundantConstraintMessage(ComputationState, Integer) - Static method in class hex.glm.ConstrainedGLMUtils

gradient(double[]) - Method in class hex.glm.GLM.GramSolver

gradient(double[]) - Method in class hex.glm.GLM.ProximalGradientSolver

gradient() - Method in class hex.glm.GLMTask.GLMMultinomialGradientBaseTask

This method changes the _gradient that is coeffPerClss by number of classes back to number of classes by coeffPerClass.

gradient(double[]) - Method in interface hex.optimization.ADMM.ProximalSolver

gradient_epsilon - Variable in class hex.schemas.GAMV3.GAMParametersV3

gradient_epsilon - Variable in class hex.schemas.GLMV3.GLMParametersV3

gradient_epsilon - Variable in class hex.schemas.ModelSelectionV3.ModelSelectionParametersV3

gradientCheck - Static variable in class hex.deeplearning.DeepLearningModelInfo

gradientCheckBias - Static variable in class hex.deeplearning.DeepLearningModelInfo

GradientInfo(double, double[]) - Constructor for class hex.optimization.OptimizationUtils.GradientInfo

gram - Variable in class hex.glm.ComputationState.GramXY

Gram - Class in hex.gram

Gram(DataInfo) - Constructor for class hex.gram.Gram

Gram(int, int, int, int, boolean) - Constructor for class hex.gram.Gram

Gram(double[][]) - Constructor for class hex.gram.Gram

Gram.Cholesky - Class in hex.gram

Gram.CollinearColumnsException - Exception in hex.gram

Gram.GramTask - Class in hex.gram

Task to compute gram matrix normalized by the number of observations (not counting rows with NAs).

Gram.InPlaceCholesky - Class in hex.gram

Gram.NonSPDMatrixException - Exception in hex.gram

Gram.OuterGramTask - Class in hex.gram

Task to compute outer product of a matrix normalized by the number of observations (not counting rows with NAs).

GramGrad(double[][], double[], double[], double, double, double[]) - Constructor for class hex.glm.ComputationState.GramGrad

GramSolver(Gram, double[], double, double, boolean) - Constructor for class hex.glm.GLM.GramSolver

GramSolver(Gram, double[], boolean, double, double, double[], double[], double[], double[]) - Constructor for class hex.glm.GLM.GramSolver

GramTask(Key<Job>, DataInfo) - Constructor for class hex.gram.Gram.GramTask

GramTask(Key<Job>, DataInfo, boolean, boolean) - Constructor for class hex.gram.Gram.GramTask

GramV3 - Class in hex.schemas

Created by tomas on 10/26/16.

GramV3() - Constructor for class hex.schemas.GramV3

GramXY(Gram, double[], double[], double[], int[], int[], double, double) - Constructor for class hex.glm.ComputationState.GramXY

Grep - Class in hex.grep

Grep model builder...

Grep(GrepModel.GrepParameters) - Constructor for class hex.grep.Grep

GrepModel - Class in hex.grep

GrepModel.GrepOutput - Class in hex.grep

GrepModel.GrepParameters - Class in hex.grep

GrepModelOutputV3() - Constructor for class hex.schemas.GrepModelV3.GrepModelOutputV3

GrepModelV3 - Class in hex.schemas

GrepModelV3() - Constructor for class hex.schemas.GrepModelV3

GrepModelV3.GrepModelOutputV3 - Class in hex.schemas

GrepOutput(Grep) - Constructor for class hex.grep.GrepModel.GrepOutput

GrepParameters() - Constructor for class hex.grep.GrepModel.GrepParameters

GrepParametersV3() - Constructor for class hex.schemas.GrepV3.GrepParametersV3

GrepV3 - Class in hex.schemas

GrepV3() - Constructor for class hex.schemas.GrepV3

GrepV3.GrepParametersV3 - Class in hex.schemas

group_column - Variable in class hex.schemas.HGLMV3.HGLMParametersV3

group_column_names - Variable in class hex.schemas.HGLMModelV3.HGLMModelOutputV3

gslvr() - Method in class hex.glm.ComputationState

gslvrMultinomial(int) - Method in class hex.glm.ComputationState

GuidedSplitPoints - Class in hex.tree

Implements a method for finding new histogram bins split-points based on a result of previous binning.

GuidedSplitPoints() - Constructor for class hex.tree.GuidedSplitPoints

H

h(Frame, String[], double, SharedTreeSubgraph[][]) - Static method in class hex.tree.FriedmanPopescusH

handlesSparseData() - Method in class hex.FrameTask2

handlesSparseData() - Method in class hex.glm.GLMTask.GLMIterationTask

hasBounds() - Method in class hex.glm.GLM.BetaConstraint

hasClosedForm(long) - Method in class hex.glrm.GLRM

hasGradient() - Method in class hex.glm.GLM.GramSolver

hasGradient() - Method in class hex.glm.GLM.ProximalGradientSolver

hasGradient() - Method in interface hex.optimization.ADMM.ProximalSolver

hash(byte[], int, int) - Method in class hex.deeplearning.MurmurHash

hashCode() - Method in class hex.rulefit.Condition

hashCode() - Method in class hex.rulefit.Rule

hashCode() - Method in class hex.tree.SharedTree.SharedTreeDebugParams

hasNABin() - Method in class hex.tree.DHistogram

hasNaNsOrInf() - Method in class hex.glm.GLMTask.GLMIterationTask

hasNaNsOrInfs() - Method in class hex.gram.Gram

hasProximalPenalty() - Method in class hex.glm.GLM.BetaConstraint

hasPValues() - Method in class hex.glm.GLMModel.GLMOutput

hasResponse() - Method in class hex.tree.isofor.IsolationForestModel.IsolationForestOutput

hasStartColumn() - Method in class hex.coxph.CoxPH

hasTreatment() - Method in class hex.generic.GenericModelOutput

hasVIF() - Method in class hex.glm.GLMModel.GLMOutput

hasZeroWeight() - Method in class hex.tree.CompressedTree

haveMojo() - Method in class hex.adaboost.AdaBoost

haveMojo() - Method in class hex.anovaglm.ANOVAGLM

haveMojo() - Method in class hex.coxph.CoxPH

haveMojo() - Method in class hex.deeplearning.DeepLearning

haveMojo() - Method in class hex.ensemble.StackedEnsemble

haveMojo() - Method in class hex.ensemble.StackedEnsembleModel

haveMojo() - Method in class hex.gam.GAM

haveMojo() - Method in class hex.generic.Generic

haveMojo() - Method in class hex.glm.GLM

haveMojo() - Method in class hex.glm.GLMModel

haveMojo() - Method in class hex.glrm.GLRM

haveMojo() - Method in class hex.hglm.HGLM

haveMojo() - Method in class hex.isotonic.IsotonicRegression

haveMojo() - Method in class hex.isotonic.IsotonicRegressionModel

haveMojo() - Method in class hex.kmeans.KMeans

haveMojo() - Method in class hex.modelselection.ModelSelection

haveMojo() - Method in class hex.naivebayes.NaiveBayes

haveMojo() - Method in class hex.pca.PCA

haveMojo() - Method in class hex.rulefit.RuleFit

haveMojo() - Method in class hex.rulefit.RuleFitModel

haveMojo() - Method in class hex.svd.SVD

haveMojo() - Method in class hex.tree.isofor.IsolationForest

haveMojo() - Method in class hex.tree.isoforextended.ExtendedIsolationForest

haveMojo() - Method in class hex.tree.SharedTree

haveMojo() - Method in class hex.tree.uplift.UpliftDRF

haveMojo() - Method in class hex.word2vec.Word2Vec

havePojo() - Method in class hex.adaboost.AdaBoost

havePojo() - Method in class hex.anovaglm.ANOVAGLM

havePojo() - Method in class hex.deeplearning.DeepLearning

havePojo() - Method in class hex.gam.GAM

havePojo() - Method in class hex.generic.GenericModel

havePojo() - Method in class hex.glm.GLM

havePojo() - Method in class hex.glm.GLMModel

havePojo() - Method in class hex.glrm.GLRM

havePojo() - Method in class hex.hglm.HGLM

havePojo() - Method in class hex.kmeans.KMeans

havePojo() - Method in class hex.modelselection.ModelSelection

havePojo() - Method in class hex.naivebayes.NaiveBayes

havePojo() - Method in class hex.pca.PCA

havePojo() - Method in class hex.svd.SVD

havePojo() - Method in class hex.tree.isofor.IsolationForest

havePojo() - Method in class hex.tree.isoforextended.ExtendedIsolationForest

havePojo() - Method in class hex.tree.SharedTree

havePojo() - Method in class hex.tree.uplift.UpliftDRF

hex - package hex

hex.adaboost - package hex.adaboost

hex.aggregator - package hex.aggregator

hex.anovaglm - package hex.anovaglm

hex.api - package hex.api

hex.coxph - package hex.coxph

hex.deeplearning - package hex.deeplearning

hex.ensemble - package hex.ensemble

hex.gam - package hex.gam

hex.gam.GamSplines - package hex.gam.GamSplines

hex.gam.MatrixFrameUtils - package hex.gam.MatrixFrameUtils

hex.generic - package hex.generic

hex.glm - package hex.glm

hex.glrm - package hex.glrm

hex.gram - package hex.gram

hex.grep - package hex.grep

hex.hglm - package hex.hglm

hex.isotonic - package hex.isotonic

hex.kmeans - package hex.kmeans

hex.modelselection - package hex.modelselection

hex.naivebayes - package hex.naivebayes

hex.optimization - package hex.optimization

hex.pca - package hex.pca

hex.pca.jama - package hex.pca.jama

hex.pca.mtj - package hex.pca.mtj

hex.psvm - package hex.psvm

hex.psvm.psvm - package hex.psvm.psvm

hex.rulefit - package hex.rulefit

hex.schemas - package hex.schemas

hex.splitframe - package hex.splitframe

hex.svd - package hex.svd

hex.tree - package hex.tree

hex.tree.drf - package hex.tree.drf

hex.tree.dt - package hex.tree.dt

hex.tree.dt.binning - package hex.tree.dt.binning

hex.tree.dt.mrtasks - package hex.tree.dt.mrtasks

hex.tree.gbm - package hex.tree.gbm

hex.tree.isofor - package hex.tree.isofor

hex.tree.isoforextended - package hex.tree.isoforextended

hex.tree.isoforextended.isolationtree - package hex.tree.isoforextended.isolationtree

hex.tree.uplift - package hex.tree.uplift

hex.util - package hex.util

hex.word2vec - package hex.word2vec

HGLM - Class in hex.hglm

HGLM(boolean) - Constructor for class hex.hglm.HGLM

HGLM(HGLMModel.HGLMParameters) - Constructor for class hex.hglm.HGLM

HGLM(HGLMModel.HGLMParameters, Key<HGLMModel>) - Constructor for class hex.hglm.HGLM

HGLMModel - Class in hex.hglm

HGLMModel(Key<HGLMModel>, HGLMModel.HGLMParameters, HGLMModel.HGLMModelOutput) - Constructor for class hex.hglm.HGLMModel

the doc = document attached to https://github.com/h2oai/h2o-3/issues/8487, title HGLM_H2O_Implementation.pdf I will be referring to the doc and different parts of it to explain my implementation.

HGLMModel.HGLMModelOutput - Class in hex.hglm

HGLMModel.HGLMParameters - Class in hex.hglm

HGLMModel.HGLMParameters.Method - Enum in hex.hglm

HGLMModelOutput(HGLM, DataInfo) - Constructor for class hex.hglm.HGLMModel.HGLMModelOutput

HGLMModelOutputV3() - Constructor for class hex.schemas.HGLMModelV3.HGLMModelOutputV3

HGLMModelV3 - Class in hex.schemas

HGLMModelV3() - Constructor for class hex.schemas.HGLMModelV3

HGLMModelV3.HGLMModelOutputV3 - Class in hex.schemas

HGLMParameters() - Constructor for class hex.hglm.HGLMModel.HGLMParameters

HGLMParametersV3() - Constructor for class hex.schemas.HGLMV3.HGLMParametersV3

HGLMScore - Class in hex.hglm

HGLMScore(Job, HGLMModel, DataInfo, String[], boolean, boolean) - Constructor for class hex.hglm.HGLMScore

HGLMTask - Class in hex.hglm

HGLMTask() - Constructor for class hex.hglm.HGLMTask

HGLMTask.ComputationEngineTask - Class in hex.hglm

This class will pre-calculate arrays (double[]) or matrices (double[][]) that will be used in later calculations that are part of the CDSS described in equation 11 of the doc.

HGLMTask.ResidualLLHTask - Class in hex.hglm

This class will calculate the residual Yj-Afj*beta-Arj*ubetaj for level 2 unit j.

HGLMUtils - Class in hex.hglm

HGLMUtils() - Constructor for class hex.hglm.HGLMUtils

HGLMV3 - Class in hex.schemas

HGLMV3() - Constructor for class hex.schemas.HGLMV3

HGLMV3.HGLMParametersV3 - Class in hex.schemas

hidden - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

The number and size of each hidden layer in the model.

hidden_dropout_ratios - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

A fraction of the inputs for each hidden layer to be omitted from training in order to improve generalization.

highest_interaction_term - Variable in class hex.schemas.ANOVAGLMV3.ANOVAGLMParametersV3

Histogram - Class in hex.tree.dt.binning

Histogram(Frame, DataFeaturesLimits, BinningStrategy) - Constructor for class hex.tree.dt.binning.Histogram

histogram_type - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3

History(int, int) - Constructor for class hex.optimization.L_BFGS.History

hyper_param - Variable in class hex.schemas.PSVMV3.PSVMParametersV3

I

icf(DataInfo, Kernel, int, double) - Static method in class hex.psvm.psvm.IncompleteCholeskyFactorization

idx_nids(int) - Method in class hex.tree.SharedTree

idx_offset() - Method in class hex.tree.SharedTree

idx_oobt() - Method in class hex.tree.SharedTree

idx_resp() - Method in class hex.tree.SharedTree

idx_treatment() - Method in class hex.tree.SharedTree

idx_tree(int) - Method in class hex.tree.SharedTree

idx_weight() - Method in class hex.tree.SharedTree

idx_work(int) - Method in class hex.tree.SharedTree

idx_xnew(int, int, int) - Static method in class hex.glrm.GLRM

idx_xold(int, int) - Static method in class hex.glrm.GLRM

idxs - Variable in class hex.glm.GLMModel.Submodel

ignoreBadColumns(int, boolean) - Method in class hex.ensemble.StackedEnsemble

ignoreBadColumns(int, boolean) - Method in class hex.word2vec.Word2Vec

ignoreInvalidColumns(int, boolean) - Method in class hex.tree.SharedTree

imp(T) - Method in class hex.tree.drf.TreeMeasuresCollector.TreeMeasures

Compute variable importance with respect to given votes.

imp(TreeMeasuresCollector.TreeSSE) - Method in class hex.tree.drf.TreeMeasuresCollector.TreeSSE

imp(TreeMeasuresCollector.TreeVotes) - Method in class hex.tree.drf.TreeMeasuresCollector.TreeVotes

Compute variable importance with respect to given votes.

importance - Variable in class hex.schemas.GLRMModelV3.GLRMModelOutputV3

importance - Variable in class hex.schemas.PCAModelV3.PCAModelOutputV3

importMojoModel(String, boolean) - Static method in class hex.generic.Generic

Convenience method for importing MOJO into H2O.

importMojoModel(URI) - Static method in class hex.generic.Generic

impute_missing - Variable in class hex.schemas.PCAV3.PCAParametersV3

impute_original - Variable in class hex.schemas.GLRMV3.GLRMParametersV3

imputeCat(Vec) - Static method in class hex.DataInfo

imputeCat(Vec, boolean) - Static method in class hex.DataInfo

imputeCat(String, Vec, boolean) - Method in interface hex.DataInfo.Imputer

imputeCat(String, Vec, boolean) - Method in class hex.DataInfo.MeanImputer

imputeCat(String, Vec, boolean) - Method in class hex.glm.GLM.PlugValuesImputer

imputeInteraction(String, InteractionWrappedVec, double[]) - Method in interface hex.DataInfo.Imputer

imputeInteraction(String, InteractionWrappedVec, double[]) - Method in class hex.DataInfo.MeanImputer

imputeInteraction(String, InteractionWrappedVec, double[]) - Method in class hex.glm.GLM.PlugValuesImputer

imputeMissing() - Method in class hex.anovaglm.ANOVAGLMModel.ANOVAGLMParameters

imputeMissing() - Method in class hex.glm.GLMModel.GLMParameters

imputeMissing() - Method in class hex.hglm.HGLMModel.HGLMParameters

imputeMissing() - Method in class hex.modelselection.ModelSelectionModel.ModelSelectionParameters

imputeNA(int) - Method in class hex.anovaglm.GenerateTransformColumns

imputeNum(String, Vec) - Method in interface hex.DataInfo.Imputer

imputeNum(String, Vec) - Method in class hex.DataInfo.MeanImputer

imputeNum(String, Vec) - Method in class hex.glm.GLM.PlugValuesImputer

in_training_checkpoints_dir - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3

in_training_checkpoints_tree_interval - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3

IncompleteCholeskyFactorization - Class in hex.psvm.psvm

Implementation of ICF based on https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/34638.pdf This implementation is based on and takes clues from the reference PSVM implementation in C++: https://code.google.com/archive/p/psvm/source/default/source original code: Copyright 2007 Google Inc., Apache License, Version 2.0

IncompleteCholeskyFactorization() - Constructor for class hex.psvm.psvm.IncompleteCholeskyFactorization

influence - Variable in class hex.schemas.GLMV3.GLMParametersV3

influence - Variable in class hex.schemas.ModelSelectionV3.ModelSelectionParametersV3

init(boolean) - Method in class hex.adaboost.AdaBoost

init(boolean) - Method in class hex.aggregator.Aggregator

init(boolean) - Method in class hex.anovaglm.ANOVAGLM

init(boolean) - Method in class hex.coxph.CoxPH

Initialize the ModelBuilder, validating all arguments and preparing the training frame.

init(boolean) - Method in class hex.deeplearning.DeepLearning

Initialize the ModelBuilder, validating all arguments and preparing the training frame.

init(Neurons[], int, DeepLearningModel.DeepLearningParameters, DeepLearningModelInfo, boolean) - Method in class hex.deeplearning.Neurons

Initialization of the parameters and connectivity of a Neuron layer

init(boolean) - Method in class hex.ensemble.StackedEnsemble

init(boolean) - Method in class hex.gam.GAM

init(boolean) - Method in class hex.generic.Generic

init(boolean) - Method in class hex.glm.GLM

init(boolean) - Method in class hex.glrm.GLRM

Validate all parameters, and prepare the model for training.

init(boolean) - Method in class hex.grep.Grep

Initialize the ModelBuilder, validating all arguments and preparing the training frame.

init(boolean) - Method in class hex.hglm.HGLM

init(boolean) - Method in class hex.isotonic.IsotonicRegression

init(boolean) - Method in class hex.kmeans.KMeans

Initialize the ModelBuilder, validating all arguments and preparing the training frame.

init(boolean) - Method in class hex.modelselection.ModelSelection

init(boolean) - Method in class hex.naivebayes.NaiveBayes

init(boolean) - Method in class hex.pca.PCA

init(boolean) - Method in class hex.psvm.PSVM

init(boolean) - Method in class hex.rulefit.RuleFit

init - Variable in class hex.schemas.CoxPHV3.CoxPHParametersV3

init - Variable in class hex.schemas.GLRMV3.GLRMParametersV3

init - Variable in class hex.schemas.KMeansV3.KMeansParametersV3

init(boolean) - Method in class hex.svd.SVD

init() - Method in class hex.tree.DHistogram

init(double[]) - Method in class hex.tree.DHistogram

init(double[], double[]) - Method in class hex.tree.DHistogram

init(boolean) - Method in class hex.tree.drf.DRF

Initialize the ModelBuilder, validating all arguments and preparing the training frame.

init(boolean) - Method in class hex.tree.gbm.GBM

Initialize the ModelBuilder, validating all arguments and preparing the training frame.

init(boolean) - Method in class hex.tree.isofor.IsolationForest

init(boolean) - Method in class hex.tree.isoforextended.ExtendedIsolationForest

init(boolean) - Method in class hex.tree.SharedTree

Initialize the ModelBuilder, validating all arguments and preparing the training frame.

init(boolean) - Method in class hex.tree.uplift.UpliftDRF

Initialize the ModelBuilder, validating all arguments and preparing the training frame.

init(boolean) - Method in class hex.word2vec.Word2Vec

Initialize the ModelBuilder, validating all arguments and preparing the training frame.

init_dispersion_parameter - Variable in class hex.schemas.GLMV3.GLMParametersV3

init_getNClass() - Method in class hex.coxph.CoxPH

init_getNClass() - Method in class hex.psvm.PSVM

init_learning_rate - Variable in class hex.schemas.Word2VecV3.Word2VecParametersV3

init_optimal_glm - Variable in class hex.schemas.GLMV3.GLMParametersV3

init_step_size - Variable in class hex.schemas.GLRMV3.GLRMParametersV3

initActualParamValues() - Method in class hex.deeplearning.DeepLearning.DeepLearningDriver

initActualParamValues() - Method in class hex.deeplearning.DeepLearningModel

initActualParamValues() - Method in class hex.ensemble.StackedEnsembleModel

initActualParamValues() - Method in class hex.glm.GLMModel

initActualParamValues() - Method in class hex.kmeans.KMeansModel

initActualParamValues() - Method in class hex.naivebayes.NaiveBayesModel

initActualParamValues() - Method in class hex.tree.drf.DRFModel

initActualParamValues() - Method in class hex.tree.gbm.GBMModel

initActualParamValues() - Method in class hex.tree.isofor.IsolationForestModel

initActualParamValues() - Method in class hex.tree.uplift.UpliftDRFModel

initActualParamValuesAfterGlmCreation() - Method in class hex.gam.GAMModel

initActualParamValuesAfterOutputSetup(boolean) - Method in class hex.tree.drf.DRFModel

initActualParamValuesAfterOutputSetup(int, boolean) - Method in class hex.tree.gbm.GBMModel

initCalibration(CalibrationHelper.ModelBuilderWithCalibration, CalibrationHelper.ParamsWithCalibration, boolean) - Static method in class hex.tree.CalibrationHelper

initCalibrationMethod(CalibrationHelper.ParamsWithCalibration) - Static method in class hex.util.EffectiveParametersUtils

initCategoricalEncoding(Model.Parameters, Model.Parameters.CategoricalEncodingScheme) - Static method in class hex.util.EffectiveParametersUtils

initConstraintDerivatives(ConstrainedGLMUtils.LinearConstraints[], ConstrainedGLMUtils.LinearConstraints[], List<String>) - Method in class hex.glm.ComputationState

This method calculates 1.

initDistribution(Model.Parameters, int) - Static method in class hex.util.EffectiveParametersUtils

initFoldAssignment(Model.Parameters) - Static method in class hex.util.EffectiveParametersUtils

initHistogramType(SharedTreeModel.SharedTreeParameters) - Static method in class hex.util.EffectiveParametersUtils

initial_biases - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

initial_fixed_effects - Variable in class hex.schemas.HGLMV3.HGLMParametersV3

initial_random_effects - Variable in class hex.schemas.HGLMV3.HGLMParametersV3

initial_t_matrix - Variable in class hex.schemas.HGLMV3.HGLMParametersV3

initial_weight_distribution - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

The distribution from which initial weights are to be drawn.

initial_weight_scale - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

The scale of the distribution function for Uniform or Normal distributions.

initial_weights - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

initialHist(Frame, int, int, DHistogram[], long, SharedTreeModel.SharedTreeParameters, Key<DHistogram.HistoSplitPoints>[], Constraints, boolean, GlobalInteractionConstraints) - Static method in class hex.tree.DHistogram

The initial histogram bins are setup from the Vec rollups.

initialInteractionConstraints(GlobalInteractionConstraints) - Method in class hex.tree.gbm.GBMModel.GBMParameters

initializeModelSpecifics() - Method in class hex.tree.SharedTree.Driver

initMetalearnerParams() - Method in class hex.ensemble.StackedEnsembleModel.StackedEnsembleParameters

initialize StackedEnsembleModel.StackedEnsembleParameters._metalearner_parameters with default parameters for the current StackedEnsembleModel.StackedEnsembleParameters._metalearner_algorithm.

initMetalearnerParams(Metalearner.Algorithm) - Method in class hex.ensemble.StackedEnsembleModel.StackedEnsembleParameters

initialize StackedEnsembleModel.StackedEnsembleParameters._metalearner_parameters with default parameters for the given algorithm

initStats(CoxPHModel, DataInfo, double[]) - Method in class hex.coxph.CoxPH.CoxPHDriver

initStoppingMetric(Model.Parameters, boolean) - Static method in class hex.util.EffectiveParametersUtils

initUpliftMetric(UpliftDRFModel.UpliftDRFParameters) - Static method in class hex.util.EffectiveParametersUtils

innerProduct(double[]) - Method in class hex.DataInfo.Row

innerProduct(double[], boolean) - Method in class hex.DataInfo.Row

innerProduct(DataInfo.Row) - Method in class hex.DataInfo.Row

innerProductChunk(DataInfo.Row, DataInfo.Row, Chunk[], Chunk[]) - Method in class hex.gram.Gram.OuterGramTask

input_dropout_ratio - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

A fraction of the features for each training row to be omitted from training in order to improve generalization (dimension sampling).

INT_NA - Static variable in class hex.tree.DHistogram

integratePolynomial(double[], double[][]) - Static method in class hex.gam.GamSplines.NBSplinesUtils

Perform integration of polynomials as described in Section VI.IV, equation 17 of doc I.

interaction_constraints - Variable in class hex.schemas.GBMV3.GBMParametersV3

interaction_pairs - Variable in class hex.schemas.CoxPHV3.CoxPHParametersV3

interaction_pairs - Variable in class hex.schemas.GAMV3.GAMParametersV3

interaction_pairs - Variable in class hex.schemas.GLMV3.GLMParametersV3

interactionBuilder() - Method in class hex.coxph.CoxPHModel.CoxPHOutput

interactionBuilder() - Method in class hex.glm.GLMModel.GLMOutput

interactionConstraints(Frame) - Method in class hex.tree.gbm.GBMModel.GBMParameters

interactions - Variable in class hex.schemas.CoxPHV3.CoxPHParametersV3

interactions - Variable in class hex.schemas.DataInfoFrameV3

interactions - Variable in class hex.schemas.GAMV3.GAMParametersV3

interactions - Variable in class hex.schemas.GLMV3.GLMParametersV3

interactions_only - Variable in class hex.schemas.CoxPHV3.CoxPHParametersV3

interactions_only - Variable in class hex.schemas.DataInfoFrameV3

interactionSpec() - Method in class hex.gam.GAMModel.GAMParameters

interactionSpec() - Method in class hex.glm.GLMModel.GLMParameters

intercept - Variable in class hex.schemas.GAMV3.GAMParametersV3

intercept - Variable in class hex.schemas.GLMV3.GLMParametersV3

intercept - Variable in class hex.schemas.ModelSelectionV3.ModelSelectionParametersV3

intercept - Variable in class hex.schemas.RuleFitModelV3.RuleFitModelOutputV3

intersection(IcedHashSet<IcedInt>) - Method in class hex.tree.BranchInteractionConstraints

Important method to decide which indices are allowed for the next level of constraints.

invalidPath() - Method in class hex.tree.SharedTreeModel.BufStringDecisionPathTracker

isAllowedIndex(int) - Method in class hex.tree.BranchInteractionConstraints

isAutoencoder() - Method in class hex.deeplearning.DeepLearningModel.DeepLearningModelOutput

isBad() - Method in class hex.DataInfo.Row

isBinomialClassifier() - Method in class hex.tree.uplift.UpliftDRFModel.UpliftDRFOutput

isCalibrated() - Method in interface hex.tree.CalibrationHelper.OutputWithCalibration

isConstant() - Method in class hex.tree.dt.binning.FeatureBins

isConstant(int) - Method in class hex.tree.dt.binning.Histogram

isDecidedRow(int) - Static method in class hex.tree.ScoreBuildHistogram

isDistributionHuber() - Method in class hex.deeplearning.DeepLearningModel

isFeatureUsedInPredict(String) - Method in class hex.deeplearning.DeepLearningModel

isFeatureUsedInPredict(int) - Method in class hex.glm.GLMModel

isFeatureUsedInPredict(int) - Method in class hex.naivebayes.NaiveBayesModel

isFeatureUsedInPredict(String) - Method in class hex.tree.SharedTreeModel

isGeneric() - Method in class hex.generic.GenericModel

isInteractionVec(int) - Method in class hex.DataInfo

isMeanAdjusted() - Method in enum hex.DataInfo.TransformType

isNAsIncluded() - Method in class hex.rulefit.Condition

IsolationForest - Class in hex.tree.isofor

Isolation Forest

IsolationForest(IsolationForestModel.IsolationForestParameters) - Constructor for class hex.tree.isofor.IsolationForest

IsolationForest(IsolationForestModel.IsolationForestParameters, Key<IsolationForestModel>) - Constructor for class hex.tree.isofor.IsolationForest

IsolationForest(IsolationForestModel.IsolationForestParameters, Job) - Constructor for class hex.tree.isofor.IsolationForest

IsolationForest(boolean) - Constructor for class hex.tree.isofor.IsolationForest

IsolationForest.VarSplits - Class in hex.tree.isofor

IsolationForestModel - Class in hex.tree.isofor

IsolationForestModel(Key<IsolationForestModel>, IsolationForestModel.IsolationForestParameters, IsolationForestModel.IsolationForestOutput) - Constructor for class hex.tree.isofor.IsolationForestModel

IsolationForestModel.IsolationForestOutput - Class in hex.tree.isofor

IsolationForestModel.IsolationForestParameters - Class in hex.tree.isofor

IsolationForestModelOutputV3() - Constructor for class hex.schemas.IsolationForestModelV3.IsolationForestModelOutputV3

IsolationForestModelV3 - Class in hex.schemas

IsolationForestModelV3() - Constructor for class hex.schemas.IsolationForestModelV3

IsolationForestModelV3.IsolationForestModelOutputV3 - Class in hex.schemas

IsolationForestMojoWriter - Class in hex.tree.isofor

Mojo definition for Isolation Forest model.

IsolationForestMojoWriter() - Constructor for class hex.tree.isofor.IsolationForestMojoWriter

IsolationForestMojoWriter(IsolationForestModel) - Constructor for class hex.tree.isofor.IsolationForestMojoWriter

IsolationForestOutput(IsolationForest) - Constructor for class hex.tree.isofor.IsolationForestModel.IsolationForestOutput

IsolationForestParameters() - Constructor for class hex.tree.isofor.IsolationForestModel.IsolationForestParameters

IsolationForestParametersV3() - Constructor for class hex.schemas.IsolationForestV3.IsolationForestParametersV3

IsolationForestV3 - Class in hex.schemas

IsolationForestV3() - Constructor for class hex.schemas.IsolationForestV3

IsolationForestV3.IsolationForestParametersV3 - Class in hex.schemas

IsolationTree - Class in hex.tree.isoforextended.isolationtree

IsolationTree class implements Algorithm 2 (iTree) Naming convention comes from the Extended Isolation Forest paper.

IsolationTree(int, int) - Constructor for class hex.tree.isoforextended.isolationtree.IsolationTree

IsolationTree.FilteredData - Class in hex.tree.isoforextended.isolationtree

IsolationTree.Node - Class in hex.tree.isoforextended.isolationtree

IsolationTree Node.

IsolationTreeStats - Class in hex.tree.isoforextended.isolationtree

Inspired by TreeStats

IsolationTreeStats() - Constructor for class hex.tree.isoforextended.isolationtree.IsolationTreeStats

isOOBRow(int) - Static method in class hex.tree.ScoreBuildHistogram

IsotonicRegression - Class in hex.isotonic

IsotonicRegression(boolean) - Constructor for class hex.isotonic.IsotonicRegression

IsotonicRegression(IsotonicRegressionModel.IsotonicRegressionParameters) - Constructor for class hex.isotonic.IsotonicRegression

IsotonicRegressionModel - Class in hex.isotonic

IsotonicRegressionModel(Key<IsotonicRegressionModel>, IsotonicRegressionModel.IsotonicRegressionParameters, IsotonicRegressionModel.IsotonicRegressionOutput) - Constructor for class hex.isotonic.IsotonicRegressionModel

IsotonicRegressionModel.IsotonicRegressionOutput - Class in hex.isotonic

IsotonicRegressionModel.IsotonicRegressionParameters - Class in hex.isotonic

IsotonicRegressionModel.OutOfBoundsHandling - Enum in hex.isotonic

IsotonicRegressionModelOutputV3() - Constructor for class hex.schemas.IsotonicRegressionModelV3.IsotonicRegressionModelOutputV3

IsotonicRegressionModelV3 - Class in hex.schemas

IsotonicRegressionModelV3() - Constructor for class hex.schemas.IsotonicRegressionModelV3

IsotonicRegressionModelV3.IsotonicRegressionModelOutputV3 - Class in hex.schemas

IsotonicRegressionMojoWriter - Class in hex.isotonic

IsotonicRegressionMojoWriter() - Constructor for class hex.isotonic.IsotonicRegressionMojoWriter

IsotonicRegressionMojoWriter(IsotonicRegressionModel) - Constructor for class hex.isotonic.IsotonicRegressionMojoWriter

IsotonicRegressionOutput(IsotonicRegression) - Constructor for class hex.isotonic.IsotonicRegressionModel.IsotonicRegressionOutput

IsotonicRegressionParameters() - Constructor for class hex.isotonic.IsotonicRegressionModel.IsotonicRegressionParameters

IsotonicRegressionParametersV3() - Constructor for class hex.schemas.IsotonicRegressionV3.IsotonicRegressionParametersV3

IsotonicRegressionV3 - Class in hex.schemas

IsotonicRegressionV3() - Constructor for class hex.schemas.IsotonicRegressionV3

IsotonicRegressionV3.IsotonicRegressionParametersV3 - Class in hex.schemas

isResponseOptional() - Method in class hex.tree.isofor.IsolationForest

isRootNode(DTree.Node) - Static method in class hex.tree.DTree

isSigmaScaled() - Method in enum hex.DataInfo.TransformType

isSparse() - Method in class hex.DataInfo.Row

isSPD() - Method in class hex.gram.Gram.Cholesky

isSPD() - Method in class hex.gram.Gram.InPlaceCholesky

isStandardized() - Method in class hex.glm.GLMModel.GLMOutput

isStochastic() - Method in class hex.tree.SharedTreeModel.SharedTreeParameters

isSupervised() - Method in class hex.adaboost.AdaBoost

isSupervised() - Method in class hex.aggregator.Aggregator

isSupervised() - Method in class hex.anovaglm.ANOVAGLM

isSupervised() - Method in class hex.coxph.CoxPH

isSupervised() - Method in class hex.deeplearning.DeepLearning

isSupervised() - Method in class hex.deeplearning.DeepLearningModel.DeepLearningModelOutput

isSupervised() - Method in class hex.ensemble.StackedEnsemble

isSupervised() - Method in class hex.gam.GAM

isSupervised() - Method in class hex.generic.Generic

isSupervised() - Method in class hex.glm.GLM

isSupervised() - Method in class hex.glm.GLMModel.GLMOutput

isSupervised() - Method in class hex.glrm.GLRM

isSupervised() - Method in class hex.grep.Grep

isSupervised() - Method in class hex.hglm.HGLM

isSupervised() - Method in class hex.isotonic.IsotonicRegression

isSupervised() - Method in class hex.modelselection.ModelSelection

isSupervised() - Method in class hex.naivebayes.NaiveBayes

isSupervised() - Method in class hex.pca.PCA

isSupervised() - Method in class hex.psvm.PSVM

isSupervised() - Method in class hex.rulefit.RuleFit

isSupervised() - Method in class hex.svd.SVD

isSupervised() - Method in class hex.tree.dt.DT

isSupervised() - Method in class hex.tree.isofor.IsolationForest

isSupervised() - Method in class hex.tree.isoforextended.ExtendedIsolationForest

isSupervised() - Method in class hex.tree.SharedTree

isSupervised() - Method in class hex.word2vec.Word2Vec

isUnstable() - Method in class hex.deeplearning.DeepLearningModelInfo

isUplift() - Method in class hex.tree.SharedTree

isUplift() - Method in class hex.tree.uplift.UpliftDRF

isUsingBinomialOpt(SharedTreeMojoModel, CompressedTree[][]) - Static method in class hex.tree.MojoUtils

isValid() - Method in class hex.optimization.OptimizationUtils.GradientInfo

isValid() - Method in class hex.tree.TreeStats

iter() - Method in class hex.glm.GLM.GramSolver

iter() - Method in class hex.glm.GLM.ProximalGradientSolver

iter() - Method in interface hex.optimization.ADMM.ProximalSolver

iter - Variable in class hex.optimization.L_BFGS.Result

iteration - Variable in class hex.glm.GLMModel.Submodel

iterations - Variable in class hex.deeplearning.DeepLearningModel

iterations - Variable in class hex.deeplearning.DeepLearningScoringInfo

iterations() - Method in class hex.deeplearning.DeepLearningScoringInfo

iterations - Variable in class hex.glm.GLMScoringInfo

iterations() - Method in class hex.glm.GLMScoringInfo

iterations - Variable in class hex.schemas.GLRMModelV3.GLRMModelOutputV3

J

javaName() - Method in class hex.adaboost.AdaBoostModel.AdaBoostParameters

javaName() - Method in class hex.aggregator.AggregatorModel.AggregatorParameters

javaName() - Method in class hex.anovaglm.ANOVAGLMModel.ANOVAGLMParameters

javaName() - Method in class hex.coxph.CoxPHModel.CoxPHParameters

javaName() - Method in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

javaName() - Method in class hex.ensemble.StackedEnsembleModel.StackedEnsembleParameters

javaName() - Method in class hex.gam.GAMModel.GAMParameters

javaName() - Method in class hex.generic.GenericModelParameters

javaName() - Method in class hex.glm.GLMModel.GLMParameters

javaName() - Method in class hex.glrm.GLRMModel.GLRMParameters

javaName() - Method in class hex.grep.GrepModel.GrepParameters

javaName() - Method in class hex.hglm.HGLMModel.HGLMParameters

javaName() - Method in class hex.isotonic.IsotonicRegressionModel.IsotonicRegressionParameters

javaName() - Method in class hex.kmeans.KMeansModel.KMeansParameters

javaName() - Method in class hex.modelselection.ModelSelectionModel.ModelSelectionParameters

javaName() - Method in class hex.naivebayes.NaiveBayesModel.NaiveBayesParameters

javaName() - Method in class hex.pca.PCAModel.PCAParameters

javaName() - Method in class hex.psvm.PSVMModel.PSVMParameters

javaName() - Method in class hex.rulefit.RuleFitModel.RuleFitParameters

javaName() - Method in class hex.svd.SVDModel.SVDParameters

javaName() - Method in class hex.tree.drf.DRFModel.DRFParameters

javaName() - Method in class hex.tree.dt.DTModel.DTParameters

javaName() - Method in class hex.tree.gbm.GBMModel.GBMParameters

javaName() - Method in class hex.tree.isofor.IsolationForestModel.IsolationForestParameters

javaName() - Method in class hex.tree.isoforextended.ExtendedIsolationForestModel.ExtendedIsolationForestParameters

javaName() - Method in class hex.tree.uplift.UpliftDRFModel.UpliftDRFParameters

javaName() - Method in class hex.word2vec.Word2VecModel.Word2VecParameters

joinDouble(double[]) - Static method in class hex.modelselection.ModelSelectionUtils

K

k() - Method in class hex.optimization.L_BFGS

k - Variable in class hex.schemas.AggregatorV99.AggregatorParametersV99

k - Variable in class hex.schemas.GLRMV3.GLRMParametersV3

k - Variable in class hex.schemas.PCAV3.PCAParametersV3

keep_gam_cols - Variable in class hex.schemas.GAMV3.GAMParametersV3

keep_levelone_frame - Variable in class hex.schemas.StackedEnsembleV99.StackedEnsembleParametersV99

keep_u - Variable in class hex.schemas.SVDV99.SVDParametersV99

keepFrameKeys(List<Key>, Key<Frame>...) - Static method in class hex.gam.MatrixFrameUtils.GamUtils

Kernel - Interface in hex.psvm.psvm

kernel() - Method in class hex.psvm.PSVMModel.PSVMParameters

kernel_type - Variable in class hex.schemas.PSVMV3.PSVMParametersV3

KernelFactory - Class in hex.psvm.psvm

KernelFactory() - Constructor for class hex.psvm.psvm.KernelFactory

KLDivergence - Class in hex.tree.uplift

KLDivergence() - Constructor for class hex.tree.uplift.KLDivergence

KMeans - Class in hex.kmeans

Scalable K-Means++ (KMeans||)
http://theory.stanford.edu/~sergei/papers/vldb12-kmpar.pdf
http://www.youtube.com/watch?v=cigXAxV3XcY

KMeans(KMeansModel.KMeansParameters) - Constructor for class hex.kmeans.KMeans

KMeans(KMeansModel.KMeansParameters, Job) - Constructor for class hex.kmeans.KMeans

KMeans(boolean) - Constructor for class hex.kmeans.KMeans

KMeans.Initialization - Enum in hex.kmeans

KMeans.IterationTask - Class in hex.kmeans

KMeansModel - Class in hex.kmeans

KMeansModel(Key, KMeansModel.KMeansParameters, KMeansModel.KMeansOutput) - Constructor for class hex.kmeans.KMeansModel

KMeansModel.KMeansOutput - Class in hex.kmeans

KMeansModel.KMeansParameters - Class in hex.kmeans

KMeansModelOutputV3() - Constructor for class hex.schemas.KMeansModelV3.KMeansModelOutputV3

KMeansModelV3 - Class in hex.schemas

KMeansModelV3() - Constructor for class hex.schemas.KMeansModelV3

KMeansModelV3.KMeansModelOutputV3 - Class in hex.schemas

KMeansMojoWriter - Class in hex.kmeans

KMeansMojoWriter() - Constructor for class hex.kmeans.KMeansMojoWriter

KMeansMojoWriter(KMeansModel) - Constructor for class hex.kmeans.KMeansMojoWriter

KMeansOutput(KMeans) - Constructor for class hex.kmeans.KMeansModel.KMeansOutput

KMeansParameters() - Constructor for class hex.kmeans.KMeansModel.KMeansParameters

KMeansParametersV3() - Constructor for class hex.schemas.KMeansV3.KMeansParametersV3

KMeansV3 - Class in hex.schemas

KMeansV3() - Constructor for class hex.schemas.KMeansV3

KMeansV3.KMeansParametersV3 - Class in hex.schemas

knot_ids - Variable in class hex.schemas.GAMV3.GAMParametersV3

L

l - Variable in class hex.glm.GLMModel.GLMWeights

l1 - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

A regularization method that constrains the absolute value of the weights and has the net effect of dropping some weights (setting them to zero) from a model to reduce complexity and avoid overfitting.

l1pen() - Method in class hex.glm.ComputationState

L1Solver(double, int, double[]) - Constructor for class hex.optimization.ADMM.L1Solver

L1Solver(double, int, double, double, double[]) - Constructor for class hex.optimization.ADMM.L1Solver

l2 - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

A regularization method that constrains the sum of the squared weights.

l2pen() - Method in class hex.glm.ComputationState

L_BFGS - Class in hex.optimization

Created by tomasnykodym on 9/15/14.

L_BFGS() - Constructor for class hex.optimization.L_BFGS

L_BFGS.History - Class in hex.optimization

Keeps L-BFGS history ie curvature information recorded over the last m steps.

L_BFGS.ProgressMonitor - Interface in hex.optimization

Monitor progress and enable early termination.

L_BFGS.Result - Class in hex.optimization

lambda() - Method in class hex.glm.ComputationState

lambda - Variable in class hex.schemas.ANOVAGLMV3.ANOVAGLMParametersV3

lambda - Variable in class hex.schemas.GAMV3.GAMParametersV3

lambda - Variable in class hex.schemas.GLMV3.GLMParametersV3

lambda - Variable in class hex.schemas.ModelSelectionV3.ModelSelectionParametersV3

lambda - Variable in class hex.schemas.RuleFitV3.RuleFitParametersV3

lambda_1se() - Method in class hex.glm.GLMModel.GLMOutput

lambda_best() - Method in class hex.glm.GLMModel.GLMOutput

lambda_min_ratio - Variable in class hex.schemas.GAMV3.GAMParametersV3

lambda_min_ratio - Variable in class hex.schemas.GLMV3.GLMParametersV3

lambda_min_ratio - Variable in class hex.schemas.ModelSelectionV3.ModelSelectionParametersV3

lambda_search - Variable in class hex.schemas.ANOVAGLMV3.ANOVAGLMParametersV3

lambda_search - Variable in class hex.schemas.GAMV3.GAMParametersV3

lambda_search - Variable in class hex.schemas.GLMV3.GLMParametersV3

lambda_search - Variable in class hex.schemas.ModelSelectionV3.ModelSelectionParametersV3

lambda_selected() - Method in class hex.glm.GLMModel.GLMOutput

lambda_value - Variable in class hex.glm.GLMModel.Submodel

lambdas - Variable in class hex.schemas.GLMRegularizationPathV3

languageCatTreshold - Variable in class hex.rulefit.Condition

languageCondition - Variable in class hex.rulefit.Condition

laplace - Variable in class hex.schemas.NaiveBayesV3.NaiveBayesParametersV3

largestCat() - Method in class hex.DataInfo

last_scored() - Method in class hex.deeplearning.DeepLearningModel

lastSpecialColumnIdx() - Method in class hex.coxph.CoxPHModel.CoxPHOutput

leaf(float) - Method in class hex.tree.TreeVisitor

LeafNode(DTree, int) - Constructor for class hex.tree.DTree.LeafNode

LeafNode(DTree, int, int) - Constructor for class hex.tree.DTree.LeafNode

LeafNode(DTree.LeafNode, DTree) - Constructor for class hex.tree.DTree.LeafNode

learn_rate - Variable in class hex.schemas.AdaBoostV3.AdaBoostParametersV3

learn_rate - Variable in class hex.schemas.GBMV3.GBMParametersV3

learn_rate_annealing - Variable in class hex.schemas.GBMV3.GBMParametersV3

left_children - Variable in class hex.schemas.TreeV3

len() - Method in class hex.tree.DTree

levels - Variable in class hex.schemas.NaiveBayesModelV3.NaiveBayesModelOutputV3

levels - Variable in class hex.schemas.TreeV3

levels - Variable in class hex.tree.TreeHandler.TreeProperties

likelihood(double, double, double[]) - Method in class hex.generic.GenericModel

likelihood - Variable in class hex.glm.ComputationState.GramXY

likelihood() - Method in class hex.glm.ComputationState

likelihood(double, double) - Method in class hex.glm.GLMModel.GLMParameters

likelihood(double, double, double[]) - Method in class hex.glm.GLMModel.GLMParameters

likelihood(double, double, double) - Method in class hex.glm.GLMModel.GLMWeightsFun

likelihood(double, double) - Method in class hex.glm.GLMModel.GLMWeightsFun

likelihood(double, double, double[]) - Method in class hex.glm.GLMModel

likelihoodAndDeviance(double, GLMModel.GLMWeights, double) - Method in class hex.glm.GLMModel.GLMWeightsFun

LIMIT_MAX - Static variable in class hex.tree.dt.NumericFeatureLimits

LIMIT_MIN - Static variable in class hex.tree.dt.NumericFeatureLimits

Linear() - Constructor for class hex.deeplearning.Neurons.Linear

linear_constraints - Variable in class hex.schemas.GLMV3.GLMParametersV3

LinearAlgebraUtils - Class in hex.util

LinearAlgebraUtils() - Constructor for class hex.util.LinearAlgebraUtils

LinearAlgebraUtils.BMulInPlaceTask - Class in hex.util

Computes B = XY where X is n by k and Y is k by p, saving result in same frame Input: [X,B] (large frame) passed to doAll, where we write to B yt = Y' = transpose of Y (small matrix) ncolX = number of columns in X

LinearAlgebraUtils.BMulTask - Class in hex.util

Computes B = XY where X is n by k and Y is k by p, saving result in new vecs Input: dinfo = X (large frame) with dinfo._adaptedFrame passed to doAll yt = Y' = transpose of Y (small matrix) Output: XY (large frame) is n by p

LinearAlgebraUtils.BMulTaskMatrices - Class in hex.util

Compute B = XY where where X is n by k and Y is k by p and they are both stored as Frames.

LinearAlgebraUtils.CopyQtoQMatrix - Class in hex.util

LinearAlgebraUtils.FindMaxIndex - Class in hex.util

LinearAlgebraUtils.ForwardSolve - Class in hex.util

Given lower triangular L, solve for Q in QL' = A (LQ' = A') using forward substitution Dimensions: A is n by p, Q is n by p, R = L' is p by p Input: [A,Q] (large frame) passed to doAll, where we write to Q

LinearAlgebraUtils.ForwardSolveInPlace - Class in hex.util

Given lower triangular L, solve for Q in QL' = A (LQ' = A') using forward substitution Dimensions: A is n by p, Q is n by p, R = L' is p by p Input: A (large frame) passed to doAll, where we overwrite each row of A with its row of Q

LinearAlgebraUtils.SMulTask - Class in hex.util

Computes A'Q where A is n by p and Q is n by k Input: [A,Q] (large frame) passed to doAll Output: atq = A'Q (small matrix) is \tilde{p} by k where \tilde{p} = number of cols in A with categoricals expanded

LinearConstraintConditions(String[], String[], double[], String[], String[], boolean) - Constructor for class hex.glm.ConstrainedGLMUtils.LinearConstraintConditions

LinearConstraints() - Constructor for class hex.glm.ConstrainedGLMUtils.LinearConstraints

link(double) - Method in class hex.glm.GLMModel.GLMWeightsFun

Given the estimated model output x, we want to find the linear part which is transpose(beta)*p+intercept if beta does not contain the intercept.

link - Variable in class hex.schemas.ANOVAGLMV3.ANOVAGLMParametersV3

link - Variable in class hex.schemas.GAMV3.GAMParametersV3

link - Variable in class hex.schemas.GLMV3.GLMParametersV3

link - Variable in class hex.schemas.ModelSelectionV3.ModelSelectionParametersV3

linkDeriv(double) - Method in class hex.glm.GLMModel.GLMParameters

linkDeriv(double) - Method in class hex.glm.GLMModel.GLMWeightsFun

linkInv(double) - Method in class hex.gam.GAMModel.GAMParameters

linkInv(double) - Method in class hex.glm.GLMModel.GLMParameters

linkInv(double) - Method in class hex.glm.GLMModel.GLMWeightsFun

Given the linear combination transpose(beta)*p+intercept (if beta does not contain the intercept), this method will provide the estimated model output.

linkInvDeriv(double) - Method in class hex.glm.GLMModel.GLMWeightsFun

linkInvDeriv2(double) - Method in class hex.glm.GLMModel.GLMWeightsFun

lmulCatBlock(double[], int) - Method in class hex.glrm.GLRM.Archetypes

lmulNumCol(double[], int) - Method in class hex.glrm.GLRM.Archetypes

loadFrames() - Method in class hex.ContributionsWithBackgroundFrameTask

loading_name - Variable in class hex.schemas.GLRMV3.GLRMParametersV3

localModelInfoKey(H2ONode) - Method in class hex.deeplearning.DeepLearningModelInfo

LOG_2PI - Static variable in class hex.hglm.MetricBuilderHGLM

logLikelihood(double, double) - Method in class hex.glm.TweedieEstimator

logLikelihood(double, double, double) - Method in class hex.glm.TweedieEstimator

logLikelihood(double, double, double, double) - Static method in class hex.glm.TweedieEstimator

logNodesHeight(Level) - Method in class hex.tree.isoforextended.isolationtree.IsolationTree

Helper method.

logNodesNumRows(Level) - Method in class hex.tree.isoforextended.isolationtree.IsolationTree

Helper method.

loss - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

The loss (error) function to be minimized by the model.

loss - Variable in class hex.schemas.GLRMV3.GLRMParametersV3

loss_by_col - Variable in class hex.schemas.GLRMV3.GLRMParametersV3

loss_by_col_idx - Variable in class hex.schemas.GLRMV3.GLRMParametersV3

lre_min - Variable in class hex.schemas.CoxPHV3.CoxPHParametersV3

LSTask(H2O.H2OCountedCompleter, DataInfo, Key) - Constructor for class hex.glm.GLMTask.LSTask

M

main(String[]) - Static method in class water.tools.MojoConvertTool

mainInternal(String[]) - Static method in class water.tools.MojoConvertTool

make(KernelType, KernelParameters) - Static method in class hex.psvm.psvm.KernelFactory

make(String, int, byte, double, double, boolean, boolean, long, SharedTreeModel.SharedTreeParameters, Key<DHistogram.HistoSplitPoints>, Constraints, boolean, double[]) - Static method in class hex.tree.DHistogram

make_model(int, MakeGLMModelV3) - Method in class hex.api.MakeGLMModelHandler

makeAdaptFrameParameters() - Method in class hex.generic.GenericModel

makeAdaptFrameParameters(Model.Parameters.CategoricalEncodingScheme) - Method in class hex.generic.GenericModel

makeAllTreeColumnNames() - Method in class hex.tree.SharedTreeModel

makeBigScoreTask(String[][], String[], Frame, boolean, boolean, Job, CFuncRef) - Method in class hex.isotonic.IsotonicRegressionModel

makeConstraintSummaryTable(GLMModel, ConstrainedGLMUtils.LinearConstraintConditions) - Static method in class hex.glm.ConstrainedGLMUtils

makeDecided(DTree.UndecidedNode, DHistogram[], Constraints) - Method in class hex.tree.isofor.IsolationForest

makeDecided(DTree.UndecidedNode, DHistogram[], Constraints) - Method in class hex.tree.SharedTree

makeDHistogramMonitor(int, int, int) - Method in class hex.tree.SharedTree.SharedTreeDebugParams

makeGAMParameters(GAMModel.GAMParameters) - Static method in class hex.gam.MatrixFrameUtils.GamUtils

MakeGLMModelHandler - Class in hex.api

Created by tomasnykodym on 3/25/15.

MakeGLMModelHandler() - Constructor for class hex.api.MakeGLMModelHandler

MakeGLMModelV3 - Class in hex.schemas

End point to update a model.

MakeGLMModelV3() - Constructor for class hex.schemas.MakeGLMModelV3

makeImputer() - Method in class hex.anovaglm.ANOVAGLMModel.ANOVAGLMParameters

makeImputer() - Method in class hex.gam.GAMModel.GAMParameters

makeImputer() - Method in class hex.glm.GLMModel.GLMParameters

makeImputer() - Method in class hex.hglm.HGLMModel.HGLMParameters

makeImputer() - Method in class hex.modelselection.ModelSelectionModel.ModelSelectionParameters

makeLeafFromNode(int[], int) - Method in class hex.tree.dt.DT

Set decision value to the node.

makeMetricBuilder(String[]) - Method in class hex.adaboost.AdaBoostModel

makeMetricBuilder(String[]) - Method in class hex.aggregator.AggregatorModel

makeMetricBuilder(String[]) - Method in class hex.anovaglm.ANOVAGLMModel

makeMetricBuilder(String[]) - Method in class hex.coxph.CoxPHModel

makeMetricBuilder(String[]) - Method in class hex.deeplearning.DeepLearningModel

makeMetricBuilder(String[]) - Method in class hex.ensemble.StackedEnsembleModel

makeMetricBuilder(String[]) - Method in class hex.gam.GAMModel

makeMetricBuilder(String[]) - Method in class hex.generic.GenericModel

makeMetricBuilder(String[]) - Method in class hex.glm.GLMModel

makeMetricBuilder(String[]) - Method in class hex.glrm.GLRMModel

makeMetricBuilder(String[]) - Method in class hex.grep.GrepModel

makeMetricBuilder(String[]) - Method in class hex.hglm.HGLMModel

makeMetricBuilder(String[]) - Method in class hex.isotonic.IsotonicRegressionModel

makeMetricBuilder(String[]) - Method in class hex.kmeans.KMeansModel

makeMetricBuilder(String[]) - Method in class hex.modelselection.ModelSelectionModel

makeMetricBuilder(String[]) - Method in class hex.naivebayes.NaiveBayesModel

makeMetricBuilder(String[]) - Method in class hex.pca.PCAModel

makeMetricBuilder(String[]) - Method in class hex.psvm.PSVMModel

makeMetricBuilder(String[]) - Method in class hex.rulefit.RuleFitModel

makeMetricBuilder(String[]) - Method in class hex.svd.SVDModel

makeMetricBuilder(String[]) - Method in class hex.tree.dt.DTModel

makeMetricBuilder(String[]) - Method in class hex.tree.isofor.IsolationForestModel

makeMetricBuilder(String[]) - Method in class hex.tree.isoforextended.ExtendedIsolationForestModel

makeMetricBuilder(String[]) - Method in class hex.tree.SharedTreeModel

makeMetricBuilder(String[]) - Method in class hex.tree.uplift.UpliftDRFModel

makeMetricBuilder(String[]) - Method in class hex.word2vec.Word2VecModel

makeModel(Key<M>, P) - Method in class hex.tree.SharedTree.Driver

makeModelMetrics(Model, Frame) - Method in class hex.aggregator.ModelMetricsAggregator.AggregatorModelMetrics

makeModelMetrics(Model, Frame, Frame, Frame) - Method in class hex.gam.MetricBuilderGAM

makeModelMetrics(Model, Frame, Frame, Frame) - Method in class hex.glm.GLMMetricBuilder

makeModelMetrics(Model, Frame) - Method in class hex.glrm.ModelMetricsGLRM.GlrmModelMetricsBuilder

makeModelMetrics(Model, Frame, Frame, Frame) - Method in class hex.hglm.MetricBuilderHGLM

makeModelMetrics(Model, Frame) - Method in class hex.pca.ModelMetricsPCA.PCAModelMetrics

makeModelMetrics(Model, Frame, Frame, Frame) - Method in class hex.psvm.MetricBuilderPSVM

Create a ModelMetrics for a given model and frame

makeModelMetrics(Model, Frame) - Method in class hex.svd.SVDModel.ModelMetricsSVD.SVDModelMetrics

makeModelMetrics() - Method in class hex.tree.dt.DT

makeModelMetrics(Model, Frame, Frame, Frame) - Method in class hex.tree.isofor.MetricBuilderAnomalySupervised

Create a ModelMetrics for a given model and frame

makeModelMetrics(Model, Frame) - Method in class hex.tree.isofor.ModelMetricsAnomaly.MetricBuilderAnomaly

makeNeuronsForTesting(DeepLearningModelInfo) - Static method in class hex.deeplearning.DeepLearningTask

makeNeuronsForTraining(DeepLearningModelInfo) - Static method in class hex.deeplearning.DeepLearningTask

makePojoWriter() - Method in class hex.generic.GenericModel

makePojoWriter(Model<?, ?, ?>, MojoModel) - Method in class hex.tree.drf.DRF

makePojoWriter(Model<?, ?, ?>, MojoModel) - Method in class hex.tree.gbm.GBM

makePojoWriter() - Method in class hex.tree.SharedTreeModel

makeScoreExtension() - Method in class hex.tree.SharedTree

makeScoreExtension() - Method in class hex.tree.uplift.UpliftDRF

makeScorer(KernelType, KernelParameters, byte[], int, boolean) - Static method in class hex.psvm.BulkScorerFactory

Creates an instance of BulkSupportVectorScorer.

makeScoringDomains(Frame, boolean, String[]) - Method in class hex.isotonic.IsotonicRegressionModel

makeScoringDomains(Frame, boolean, String[]) - Method in class hex.tree.isofor.IsolationForestModel

makeScoringDomains(Frame, boolean, String[]) - Method in class hex.tree.isoforextended.ExtendedIsolationForestModel

makeScoringNames() - Method in class hex.adaboost.AdaBoostModel

makeScoringNames() - Method in class hex.gam.GAMModel

makeScoringNames() - Method in class hex.generic.GenericModel

makeScoringNames() - Method in class hex.glm.GLMModel

makeScoringNames() - Method in class hex.hglm.HGLMModel

makeScoringNames() - Method in class hex.isotonic.IsotonicRegressionModel

makeScoringNames() - Method in class hex.tree.isofor.IsolationForestModel

makeScoringNames() - Method in class hex.tree.isoforextended.ExtendedIsolationForestModel

makeTreeKey(int, int) - Static method in class hex.tree.CompressedTree

makeTreePojoWriter() - Method in class hex.tree.drf.DRFModel

makeTreePojoWriter() - Method in class hex.tree.gbm.GBMModel

makeTreePojoWriter() - Method in class hex.tree.SharedTreeModel

makeUndecidedNode(DHistogram[], Constraints, BranchInteractionConstraints) - Method in class hex.tree.DTree.DecidedNode

makeValidWorkspace() - Method in class hex.tree.SharedTree.Driver

makeZeros(double[], double[]) - Static method in class hex.glm.DispersionUtils

map(Chunk[], NewChunk[]) - Method in class hex.anovaglm.GenerateTransformColumns

map(Chunk[], NewChunk[]) - Method in class hex.ContributionsMeanAggregator

map(Chunk[], NewChunk[]) - Method in class hex.ContributionsWithBackgroundFrameTask

map(Chunk[], Chunk[], NewChunk[]) - Method in class hex.ContributionsWithBackgroundFrameTask

map(Chunk[]) - Method in class hex.FrameTask.ExtractDenseRow

map(Chunk[], NewChunk[]) - Method in class hex.FrameTask

Extracts the values, applies regularization to numerics, adds appropriate offsets to categoricals, and adapts response according to the CaseMode/CaseValue if set.

map(Chunk[]) - Method in class hex.FrameTask2

map(Chunk[], NewChunk[]) - Method in class hex.gam.GamSplines.ThinPlateDistanceWithKnots

map(Chunk[], NewChunk[]) - Method in class hex.gam.GamSplines.ThinPlatePolynomialWithKnots

map(Chunk[], NewChunk[]) - Method in class hex.gam.GamSplines.ThinPlateRegressionUtils.ScaleTPPenalty

map(Chunk[], NewChunk[]) - Method in class hex.gam.MatrixFrameUtils.AddCSGamColumns

map(Chunk[], NewChunk[]) - Method in class hex.gam.MatrixFrameUtils.AddISGamColumns

map(Chunk[], NewChunk[]) - Method in class hex.gam.MatrixFrameUtils.AddMSGamColumns

map(Chunk[], NewChunk[]) - Method in class hex.gam.MatrixFrameUtils.GenCSSplineGamOneColumn

map(Chunk[], NewChunk[]) - Method in class hex.gam.MatrixFrameUtils.GenISplineGamOneColumn

map(Chunk[], NewChunk[]) - Method in class hex.gam.MatrixFrameUtils.GenMSplineGamOneColumn

map(Chunk[]) - Method in class hex.glm.DispersionTask.ComputeMaxSumSeriesTsk

map(Chunk[], NewChunk[]) - Method in class hex.glm.DispersionTask.ComputeTweedieConstTsk

map(Chunk[], NewChunk[]) - Method in class hex.glm.DispersionTask.GenPrediction

map(Chunk[], NewChunk[]) - Method in class hex.glm.GLMScore

map(Chunk[]) - Method in class hex.glm.GLMTask.GLMCoordinateDescentTaskSeqIntercept

map(Chunk[]) - Method in class hex.glm.GLMTask.GLMCoordinateDescentTaskSeqNaive

map(Chunk[]) - Method in class hex.glm.GLMTask.GLMGenerateWeightsTask

map(Chunk[]) - Method in class hex.glm.GLMTask.GLMMultinomialGradientBaseTask

map(Chunk[]) - Method in class hex.glm.GLMTask.GLMMultinomialUpdate

map(Chunk[]) - Method in class hex.glm.GLMTask.YMUTask

map(Chunk[], NewChunk[]) - Method in class hex.glm.RegressionInfluenceDiagnosticsTasks.ComputeNewBetaVarEstimatedGaussian

map(Chunk[], NewChunk[]) - Method in class hex.glm.RegressionInfluenceDiagnosticsTasks.RegressionInfluenceDiagBinomial

map(Chunk[], NewChunk[]) - Method in class hex.glm.RegressionInfluenceDiagnosticsTasks.RegressionInfluenceDiagGaussian

map(Chunk[]) - Method in class hex.glm.TweedieEstimator

map(Chunk[]) - Method in class hex.glrm.GLRM.updateXVecs

map(Chunk[], NewChunk[]) - Method in class hex.glrm.GLRMGenX

map(Chunk[]) - Method in class hex.gram.Gram.OuterGramTask

map(Chunk[], NewChunk[]) - Method in class hex.hglm.HGLMScore

map(Chunk[]) - Method in class hex.hglm.HGLMTask.ComputationEngineTask

map(Chunk[]) - Method in class hex.hglm.HGLMTask.ResidualLLHTask

map(Chunk[]) - Method in class hex.modelselection.ModelSelectionTasks.SweepFrameParallel

map(Chunk[], byte[]) - Method in class hex.rulefit.Condition

map(Chunk[], byte[]) - Method in class hex.rulefit.Rule

map(Chunk[]) - Method in class hex.tree.drf.TreeMeasuresCollector

map(Chunk, Chunk) - Method in class hex.tree.drf.TreeMeasuresCollector.ShuffleTask

map(Chunk[]) - Method in class hex.tree.dt.mrtasks.CountBinsSamplesCountsMRTask

map(Chunk[], NewChunk[]) - Method in class hex.tree.dt.mrtasks.FeaturesLimitsMRTask

map(Chunk[]) - Method in class hex.tree.dt.mrtasks.GetClassCountsMRTask

map(Chunk[]) - Method in class hex.tree.dt.mrtasks.ScoreDTTask

map(Chunk[]) - Method in class hex.tree.ExactSplitPoints

map(Chunk[]) - Method in class hex.tree.gbm.GBM.DiffMinusMedianDiff

map(Chunk[]) - Method in class hex.tree.ReconstructTreeState

map(Chunk, Chunk) - Method in class hex.tree.Sample

map(Chunk[]) - Method in class hex.tree.Score

map(Chunk[]) - Method in class hex.tree.ScoreBuildHistogram2

map(Chunk[], NewChunk[]) - Method in class hex.tree.SharedTreeModelWithContributions.ScoreContributionsSortingTask

map(Chunk[], NewChunk[]) - Method in class hex.tree.SharedTreeModelWithContributions.ScoreContributionsTask

map(Chunk[], Chunk[], NewChunk[]) - Method in class hex.tree.SharedTreeModelWithContributions.ScoreContributionsWithBackgroundTask

map(Chunk[]) - Method in class hex.util.LinearAlgebraUtils.BMulInPlaceTask

map(Chunk[]) - Method in class hex.util.LinearAlgebraUtils.BMulTaskMatrices

map(Chunk[]) - Method in class hex.util.LinearAlgebraUtils.CopyQtoQMatrix

map(Chunk[]) - Method in class hex.util.LinearAlgebraUtils.FindMaxIndex

map(Chunk[]) - Method in class hex.util.LinearAlgebraUtils.ForwardSolve

map(Chunk[]) - Method in class hex.util.LinearAlgebraUtils.ForwardSolveInPlace

map(Chunk[]) - Method in class hex.util.LinearAlgebraUtils.SMulTask

map(Chunk) - Method in class hex.word2vec.WordCountTask

map(Chunk[]) - Method in class hex.word2vec.WordVectorConverter

map(Chunk) - Method in class hex.word2vec.WordVectorTrainer

mapBasicVector2Multiple(ModelSelectionUtils.SweepVector[][], int) - Static method in class hex.modelselection.ModelSelectionUtils

When multiple rows/columns are added to the CPM due to the new predictor being categorical, we need to map the old sweep vector arrays to new bigger sweep vector arrays.

mapNames(String[]) - Method in class hex.DataInfo

mapping_frame - Variable in class hex.schemas.AggregatorModelV99.AggregatorModelOutputV99

mapPredIndex2CPMIndices(DataInfo, int, List<Integer>) - Static method in class hex.modelselection.ModelSelectionUtils

This method attempts to map all predictors into the corresponding cpm indices that refer to that predictor.

match(double[], int[]) - Method in class hex.glm.ComputationState.GramXY

matches - Variable in class hex.schemas.GrepModelV3.GrepModelOutputV3

matrixMultiply(double[][], double[][]) - Static method in class hex.util.LinearAlgebraUtils

matrixMultiplyTriagonal(double[][], TriDiagonalMatrix, boolean) - Static method in class hex.util.LinearAlgebraUtils

MatrixUtils - Class in hex.psvm.psvm

Utils class for matrix operations.

MatrixUtils() - Constructor for class hex.psvm.psvm.MatrixUtils

max_abs_leafnode_pred - Variable in class hex.schemas.GBMV3.GBMParametersV3

max_active_predictors - Variable in class hex.schemas.GAMV3.GAMParametersV3

max_active_predictors - Variable in class hex.schemas.GLMV3.GLMParametersV3

max_active_predictors - Variable in class hex.schemas.ModelSelectionV3.ModelSelectionParametersV3

max_after_balance_size - Variable in class hex.schemas.ANOVAGLMV3.ANOVAGLMParametersV3

When classes are balanced, limit the resulting dataset size to the specified multiple of the original dataset size.

max_after_balance_size - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

When classes are balanced, limit the resulting dataset size to the specified multiple of the original dataset size.

max_after_balance_size - Variable in class hex.schemas.GAMV3.GAMParametersV3

When classes are balanced, limit the resulting dataset size to the specified multiple of the original dataset size.

max_after_balance_size - Variable in class hex.schemas.GLMV3.GLMParametersV3

When classes are balanced, limit the resulting dataset size to the specified multiple of the original dataset size.

max_after_balance_size - Variable in class hex.schemas.ModelSelectionV3.ModelSelectionParametersV3

When classes are balanced, limit the resulting dataset size to the specified multiple of the original dataset size.

max_after_balance_size - Variable in class hex.schemas.NaiveBayesV3.NaiveBayesParametersV3

When classes are balanced, limit the resulting dataset size to the specified multiple of the original dataset size.

max_after_balance_size - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3

When classes are balanced, limit the resulting dataset size to the specified multiple of the original dataset size.

max_categorical_features - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

max_confusion_matrix_size - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

For classification models, the maximum size (in terms of classes) of the confusion matrix for it to be printed.

max_confusion_matrix_size - Variable in class hex.schemas.GAMV3.GAMParametersV3

For classification models, the maximum size (in terms of classes) of the confusion matrix for it to be printed.

max_confusion_matrix_size - Variable in class hex.schemas.GLMV3.GLMParametersV3

For classification models, the maximum size (in terms of classes) of the confusion matrix for it to be printed.

max_confusion_matrix_size - Variable in class hex.schemas.ModelSelectionV3.ModelSelectionParametersV3

For classification models, the maximum size (in terms of classes) of the confusion matrix for it to be printed.

max_confusion_matrix_size - Variable in class hex.schemas.NaiveBayesV3.NaiveBayesParametersV3

For classification models, the maximum size (in terms of classes) of the confusion matrix for it to be printed.

max_confusion_matrix_size - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3

For classification models, the maximum size (in terms of classes) of the confusion matrix for it to be printed.

max_depth - Variable in class hex.schemas.DTV3.DTParametersV3

max_depth - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3

max_depth - Variable in class hex.schemas.TreeStatsV3

MAX_INDEX - Static variable in class hex.tree.dt.binning.NumericBin

max_iterations - Variable in class hex.schemas.AggregatorV99.AggregatorParametersV99

max_iterations - Variable in class hex.schemas.ANOVAGLMV3.ANOVAGLMParametersV3

max_iterations - Variable in class hex.schemas.CoxPHV3.CoxPHParametersV3

max_iterations - Variable in class hex.schemas.GAMV3.GAMParametersV3

max_iterations - Variable in class hex.schemas.GLMV3.GLMParametersV3

max_iterations - Variable in class hex.schemas.GLRMV3.GLRMParametersV3

max_iterations - Variable in class hex.schemas.HGLMV3.HGLMParametersV3

max_iterations - Variable in class hex.schemas.KMeansV3.KMeansParametersV3

max_iterations - Variable in class hex.schemas.ModelSelectionV3.ModelSelectionParametersV3

max_iterations - Variable in class hex.schemas.PCAV3.PCAParametersV3

max_iterations - Variable in class hex.schemas.PSVMV3.PSVMParametersV3

max_iterations - Variable in class hex.schemas.SVDV99.SVDParametersV99

max_iterations_dispersion - Variable in class hex.schemas.GLMV3.GLMParametersV3

max_leaves - Variable in class hex.schemas.TreeStatsV3

MAX_NTREES - Static variable in class hex.tree.isoforextended.ExtendedIsolationForest

MAX_NTREES - Static variable in class hex.tree.SharedTree

max_num_rules - Variable in class hex.schemas.RuleFitV3.RuleFitParametersV3

max_predictor_number - Variable in class hex.schemas.ModelSelectionV3.ModelSelectionParametersV3

max_rule_length - Variable in class hex.schemas.RuleFitV3.RuleFitParametersV3

MAX_SAMPLE_SIZE - Static variable in class hex.tree.isoforextended.ExtendedIsolationForest

max_updates - Variable in class hex.schemas.GLRMV3.GLRMParametersV3

max_w2 - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

A maximum on the sum of the squared incoming weights into any one neuron.

max_x - Variable in class hex.schemas.IsotonicRegressionModelV3.IsotonicRegressionModelOutputV3

maxIter() - Method in class hex.optimization.L_BFGS

Maxout(DeepLearningModel.DeepLearningParameters, short, int) - Constructor for class hex.deeplearning.Neurons.Maxout

MaxoutDropout(DeepLearningModel.DeepLearningParameters, short, int) - Constructor for class hex.deeplearning.Neurons.MaxoutDropout

mean_a - Variable in class hex.deeplearning.DeepLearningModelInfo

mean_depth - Variable in class hex.schemas.TreeStatsV3

mean_leaves - Variable in class hex.schemas.TreeStatsV3

mean_normalized_score - Variable in class water.api.ModelMetricsAnomalyV3

mean_score - Variable in class water.api.ModelMetricsAnomalyV3

MeanImputer() - Constructor for class hex.DataInfo.MeanImputer

meanLoss(DataInfo.Row[]) - Method in class hex.deeplearning.DeepLearningModel

Compute the loss function

mergeCombos(ArrayList<int[]>, Integer[], int[], List<Integer[]>) - Static method in class hex.gam.GamSplines.ThinPlateRegressionUtils

mergeWith(TreeStats) - Method in class hex.tree.TreeStats

messages - Variable in class hex.optimization.OptimizationUtils.MoreThuente

Metalearner<B extends hex.ModelBuilder<M,P,?>,M extends hex.Model<M,P,?>,P extends hex.Model.Parameters> - Class in hex.ensemble

Metalearner() - Constructor for class hex.ensemble.Metalearner

Metalearner.Algorithm - Enum in hex.ensemble

Using an enum to list possible algos is not the greatest idea here as it forces us to hardcode supported algos and creates a dependency to metalearners provided in extensions (XGBoost).

metalearner_algorithm - Variable in class hex.schemas.StackedEnsembleV99.StackedEnsembleParametersV99

metalearner_fold_assignment - Variable in class hex.schemas.StackedEnsembleV99.StackedEnsembleParametersV99

metalearner_fold_column - Variable in class hex.schemas.StackedEnsembleV99.StackedEnsembleParametersV99

metalearner_nfolds - Variable in class hex.schemas.StackedEnsembleV99.StackedEnsembleParametersV99

metalearner_params - Variable in class hex.schemas.StackedEnsembleV99.StackedEnsembleParametersV99

metalearner_transform - Variable in class hex.schemas.StackedEnsembleV99.StackedEnsembleParametersV99

MetalearnerProvider<M extends Metalearner> - Interface in hex.ensemble

Metalearners - Class in hex.ensemble

Entry point class to load and access the supported metalearners.

Metalearners() - Constructor for class hex.ensemble.Metalearners

Metalearners.SimpleMetalearner - Class in hex.ensemble

A simple implementation of Metalearner suitable for any algo; it is just using the algo with its default parameters.

method - Variable in class hex.schemas.HGLMV3.HGLMParametersV3

metric(double, double) - Method in class hex.tree.uplift.ChiSquaredDivergence

metric(double, double) - Method in class hex.tree.uplift.Divergence

Calculate distance divergence metric between two probabilities.

metric(double, double) - Method in class hex.tree.uplift.EuclideanDistance

metric(double, double) - Method in class hex.tree.uplift.KLDivergence

MetricBuilderAnomaly() - Constructor for class hex.tree.isofor.ModelMetricsAnomaly.MetricBuilderAnomaly

MetricBuilderAnomaly(String, boolean) - Constructor for class hex.tree.isofor.ModelMetricsAnomaly.MetricBuilderAnomaly

MetricBuilderAnomalySupervised - Class in hex.tree.isofor

MetricBuilderAnomalySupervised(String[]) - Constructor for class hex.tree.isofor.MetricBuilderAnomalySupervised

MetricBuilderGAM - Class in hex.gam

MetricBuilderGAM(String[], double[], GLMModel.GLMWeightsFun, int, boolean, boolean, int, MultinomialAucType) - Constructor for class hex.gam.MetricBuilderGAM

MetricBuilderHGLM - Class in hex.hglm

MetricBuilderHGLM(String[], boolean, boolean, boolean, HGLMModel.HGLMModelOutput) - Constructor for class hex.hglm.MetricBuilderHGLM

MetricBuilderPSVM<T extends MetricBuilderPSVM<T>> - Class in hex.psvm

Binomial Metric builder tailored to SVM SVM doesn't predict probabilities, only probabilities 0-1 are returned, this renders some binomial metric misleading (eg.

MetricBuilderPSVM(String[]) - Constructor for class hex.psvm.MetricBuilderPSVM

mid(int, float, int) - Method in class hex.tree.TreeVisitor

min_depth - Variable in class hex.schemas.TreeStatsV3

MIN_IMPROVEMENT - Static variable in class hex.tree.dt.DT

MIN_INDEX - Static variable in class hex.tree.dt.binning.NumericBin

min_leaves - Variable in class hex.schemas.TreeStatsV3

min_predictor_number - Variable in class hex.schemas.ModelSelectionV3.ModelSelectionParametersV3

min_prob - Variable in class hex.schemas.NaiveBayesV3.NaiveBayesParametersV3

min_rows - Variable in class hex.schemas.DTV3.DTParametersV3

min_rows - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3

min_rule_length - Variable in class hex.schemas.RuleFitV3.RuleFitParametersV3

min_sdev - Variable in class hex.schemas.NaiveBayesV3.NaiveBayesParametersV3

min_split_improvement - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3

min_step_size - Variable in class hex.schemas.GLRMV3.GLRMParametersV3

min_word_freq - Variable in class hex.schemas.Word2VecV3.Word2VecParametersV3

min_x - Variable in class hex.schemas.IsotonicRegressionModelV3.IsotonicRegressionModelOutputV3

mini_batch_size - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

minMemoryPerNode() - Static method in class hex.ContributionsWithBackgroundFrameTask

missing_values_handling - Variable in class hex.schemas.ANOVAGLMV3.ANOVAGLMParametersV3

missing_values_handling - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

missing_values_handling - Variable in class hex.schemas.GAMV3.GAMParametersV3

missing_values_handling - Variable in class hex.schemas.GLMV3.GLMParametersV3

missing_values_handling - Variable in class hex.schemas.HGLMV3.HGLMParametersV3

missing_values_handling - Variable in class hex.schemas.ModelSelectionV3.ModelSelectionParametersV3

missingColumnsType() - Method in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

missingValuesHandling() - Method in class hex.anovaglm.ANOVAGLMModel.ANOVAGLMParameters

missingValuesHandling() - Method in class hex.gam.GAMModel.GAMParameters

missingValuesHandling() - Method in class hex.glm.GLMModel.GLMParameters

missingValuesHandling() - Method in class hex.hglm.HGLMModel.HGLMParameters

missingValuesHandling() - Method in class hex.modelselection.ModelSelectionModel.ModelSelectionParameters

mode - Variable in class hex.schemas.ModelSelectionV3.ModelSelectionParametersV3

model - Variable in class hex.schemas.GLMRegularizationPathV3

model - Variable in class hex.schemas.MakeGLMModelV3

model - Variable in class hex.schemas.TreeV3

model - Variable in class hex.schemas.Word2VecSynonymsV3

model - Variable in class hex.schemas.Word2VecTransformV3

model_info() - Method in class hex.deeplearning.DeepLearningModel

model_info() - Method in class hex.deeplearning.DeepLearningTask

Accessor to the object containing the (final) state of the Deep Learning model Should only be queried after calling this.doAll(Frame training)

model_info() - Method in class hex.deeplearning.DeepLearningTask2

Returns the aggregated DeepLearning model that was trained by all nodes (over all the training data)

model_info_key - Variable in class hex.deeplearning.DeepLearningModel

model_key - Variable in class hex.schemas.GenericV3.GenericParametersV3

model_type - Variable in class hex.schemas.RuleFitV3.RuleFitParametersV3

modelCategory - Variable in class hex.ensemble.StackedEnsembleModel

modelDescriptor() - Method in class hex.coxph.CoxPHModel

ModelMetricsAggregator - Class in hex.aggregator

ModelMetricsAggregator(Model, Frame, CustomMetric) - Constructor for class hex.aggregator.ModelMetricsAggregator

ModelMetricsAggregator.AggregatorModelMetrics - Class in hex.aggregator

ModelMetricsAnomaly - Class in hex.tree.isofor

ModelMetricsAnomaly(Model, Frame, CustomMetric, long, double, double, String) - Constructor for class hex.tree.isofor.ModelMetricsAnomaly

ModelMetricsAnomaly.MetricBuilderAnomaly - Class in hex.tree.isofor

ModelMetricsAnomalyV3 - Class in water.api

ModelMetricsAnomalyV3() - Constructor for class water.api.ModelMetricsAnomalyV3

ModelMetricsGLRM - Class in hex.glrm

ModelMetricsGLRM(Model, Frame, double, double, CustomMetric) - Constructor for class hex.glrm.ModelMetricsGLRM

ModelMetricsGLRM(Model, Frame, double, double, long, long, CustomMetric) - Constructor for class hex.glrm.ModelMetricsGLRM

ModelMetricsGLRM.GlrmModelMetricsBuilder - Class in hex.glrm

ModelMetricsGLRMV99 - Class in water.api

ModelMetricsGLRMV99() - Constructor for class water.api.ModelMetricsGLRMV99

ModelMetricsPCA - Class in hex.pca

ModelMetricsPCA(Model, Frame, CustomMetric) - Constructor for class hex.pca.ModelMetricsPCA

ModelMetricsPCA.PCAModelMetrics - Class in hex.pca

ModelMetricsPCAV3 - Class in water.api

ModelMetricsPCAV3() - Constructor for class water.api.ModelMetricsPCAV3

ModelMetricsSVD(Model, Frame, CustomMetric) - Constructor for class hex.svd.SVDModel.ModelMetricsSVD

ModelMetricsSVDV99 - Class in water.api

ModelMetricsSVDV99() - Constructor for class water.api.ModelMetricsSVDV99

models - Variable in class hex.adaboost.AdaBoostModel.AdaBoostOutput

ModelSelection - Class in hex.modelselection

ModelSelection(boolean) - Constructor for class hex.modelselection.ModelSelection

ModelSelection(ModelSelectionModel.ModelSelectionParameters) - Constructor for class hex.modelselection.ModelSelection

ModelSelection(ModelSelectionModel.ModelSelectionParameters, Key<ModelSelectionModel>) - Constructor for class hex.modelselection.ModelSelection

ModelSelection.ModelSelectionDriver - Class in hex.modelselection

ModelSelection.SweepModel - Class in hex.modelselection

Contains information of a predictor subsets like predictor indices of the subset (with the newest predictor as the last element of the array), CPM associated with predictor subset minus the latest element and the error variance of the CPM.

ModelSelectionDriver() - Constructor for class hex.modelselection.ModelSelection.ModelSelectionDriver

ModelSelectionModel - Class in hex.modelselection

ModelSelectionModel(Key<ModelSelectionModel>, ModelSelectionModel.ModelSelectionParameters, ModelSelectionModel.ModelSelectionModelOutput) - Constructor for class hex.modelselection.ModelSelectionModel

ModelSelectionModel.ModelSelectionModelOutput - Class in hex.modelselection

ModelSelectionModel.ModelSelectionParameters - Class in hex.modelselection

ModelSelectionModel.ModelSelectionParameters.Mode - Enum in hex.modelselection

ModelSelectionModelOutput(ModelSelection, DataInfo) - Constructor for class hex.modelselection.ModelSelectionModel.ModelSelectionModelOutput

ModelSelectionModelOutputV3() - Constructor for class hex.schemas.ModelSelectionModelV3.ModelSelectionModelOutputV3

ModelSelectionModelV3 - Class in hex.schemas

ModelSelectionModelV3() - Constructor for class hex.schemas.ModelSelectionModelV3

ModelSelectionModelV3.ModelSelectionModelOutputV3 - Class in hex.schemas

ModelSelectionModeProvider() - Constructor for class hex.schemas.ModelSelectionV3.ModelSelectionModeProvider

ModelSelectionParameters() - Constructor for class hex.modelselection.ModelSelectionModel.ModelSelectionParameters

ModelSelectionParametersV3() - Constructor for class hex.schemas.ModelSelectionV3.ModelSelectionParametersV3

ModelSelectionTasks - Class in hex.modelselection

ModelSelectionTasks() - Constructor for class hex.modelselection.ModelSelectionTasks

ModelSelectionTasks.SweepFrameParallel - Class in hex.modelselection

ModelSelectionUtils - Class in hex.modelselection

ModelSelectionUtils() - Constructor for class hex.modelselection.ModelSelectionUtils

ModelSelectionUtils.SweepVector - Class in hex.modelselection

store information on sweeping actions that are to be performed to new rows/columns added to CPM due to the addition of new predcitors.

ModelSelectionV3 - Class in hex.schemas

ModelSelectionV3() - Constructor for class hex.schemas.ModelSelectionV3

ModelSelectionV3.ModelSelectionModeProvider - Class in hex.schemas

ModelSelectionV3.ModelSelectionParametersV3 - Class in hex.schemas

modifiesVolatileVecs() - Method in class hex.tree.Score

MojoConvertTool - Class in water.tools

Convenience command line tool for converting H2O MOJO to POJO

MojoConvertTool(File, File) - Constructor for class water.tools.MojoConvertTool

MojoUtils - Class in hex.tree

MojoUtils() - Constructor for class hex.tree.MojoUtils

mojoVersion() - Method in class hex.coxph.CoxPHMojoWriter

mojoVersion() - Method in class hex.deeplearning.DeepLearningMojoWriter

mojoVersion() - Method in class hex.ensemble.StackedEnsembleMojoWriter

mojoVersion() - Method in class hex.gam.GAMMojoWriter

mojoVersion() - Method in class hex.generic.GenericModelMojoWriter

mojoVersion() - Method in class hex.glm.GLMMojoWriter

mojoVersion() - Method in class hex.glrm.GlrmMojoWriter

mojoVersion() - Method in class hex.isotonic.IsotonicRegressionMojoWriter

mojoVersion() - Method in class hex.kmeans.KMeansMojoWriter

mojoVersion() - Method in class hex.pca.PCAMojoWriter

mojoVersion() - Method in class hex.rulefit.RuleFitMojoWriter

mojoVersion() - Method in class hex.tree.drf.DrfMojoWriter

mojoVersion() - Method in class hex.tree.gbm.GbmMojoWriter

mojoVersion() - Method in class hex.tree.isofor.IsolationForestMojoWriter

mojoVersion() - Method in class hex.tree.isoforextended.ExtendedIsolationForestMojoWriter

mojoVersion() - Method in class hex.tree.uplift.UpliftDrfMojoWriter

mojoVersion() - Method in class hex.word2vec.Word2VecMojoWriter

momentum() - Method in class hex.deeplearning.Neurons

momentum(double) - Method in class hex.deeplearning.Neurons

The momentum - real number in [0, 1) Can be a linear ramp from momentum_start to momentum_stable, over momentum_ramp training samples

momentum_ramp - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

The momentum_ramp parameter controls the amount of learning for which momentum increases (assuming momentum_stable is larger than momentum_start).

momentum_stable - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

The momentum_stable parameter controls the final momentum value reached after momentum_ramp training samples.

momentum_start - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

The momentum_start parameter controls the amount of momentum at the beginning of training.

monotone_constraints - Variable in class hex.schemas.GBMV3.GBMParametersV3

MoreThuente(OptimizationUtils.GradientSolver, double[]) - Constructor for class hex.optimization.OptimizationUtils.MoreThuente

MoreThuente(OptimizationUtils.GradientSolver, double[], OptimizationUtils.GradientInfo) - Constructor for class hex.optimization.OptimizationUtils.MoreThuente

MoreThuente(OptimizationUtils.GradientSolver, double[], OptimizationUtils.GradientInfo, double, double, double) - Constructor for class hex.optimization.OptimizationUtils.MoreThuente

mtries - Variable in class hex.schemas.DRFV3.DRFParametersV3

mtries - Variable in class hex.schemas.IsolationForestV3.IsolationForestParametersV3

mtries - Variable in class hex.schemas.UpliftDRFV3.UpliftDRFParametersV3

mtrxMul(double[][], double[]) - Method in class hex.DataInfo.Row

mu - Variable in class hex.glm.GLMModel.GLMWeights

mu_factor - Variable in class hex.schemas.PSVMV3.PSVMParametersV3

MUIND - Static variable in class hex.glm.DispersionTask

mul(double) - Method in class hex.gram.Gram

mul(double[]) - Method in class hex.gram.Gram

mul(double[], double[]) - Method in class hex.gram.Gram

mult(double) - Method in class hex.deeplearning.DeepLearningModelInfo

Multiply all weights/biases by a real-valued number

multi_loss - Variable in class hex.schemas.GLRMV3.GLRMParametersV3

multiClassCoeffNames() - Method in class hex.glm.GLMModel.GLMOutput

multinode_mode - Variable in class hex.schemas.ModelSelectionV3.ModelSelectionParametersV3

MurmurHash - Class in hex.deeplearning

This is a very fast, non-cryptographic hash suitable for general hash-based lookup.

MurmurHash() - Constructor for class hex.deeplearning.MurmurHash

N

n0() - Method in class hex.tree.DTree.Split

n1() - Method in class hex.tree.DTree.Split

NaiveBayes - Class in hex.naivebayes

Naive Bayes This is an algorithm for computing the conditional a-posterior probabilities of a categorical response from independent predictors using Bayes rule.

NaiveBayes(NaiveBayesModel.NaiveBayesParameters) - Constructor for class hex.naivebayes.NaiveBayes

NaiveBayes(boolean) - Constructor for class hex.naivebayes.NaiveBayes

NaiveBayesModel - Class in hex.naivebayes

NaiveBayesModel(Key, NaiveBayesModel.NaiveBayesParameters, NaiveBayesModel.NaiveBayesOutput) - Constructor for class hex.naivebayes.NaiveBayesModel

NaiveBayesModel.NaiveBayesOutput - Class in hex.naivebayes

NaiveBayesModel.NaiveBayesParameters - Class in hex.naivebayes

NaiveBayesModelOutputV3() - Constructor for class hex.schemas.NaiveBayesModelV3.NaiveBayesModelOutputV3

NaiveBayesModelV3 - Class in hex.schemas

NaiveBayesModelV3() - Constructor for class hex.schemas.NaiveBayesModelV3

NaiveBayesModelV3.NaiveBayesModelOutputV3 - Class in hex.schemas

NaiveBayesOutput(NaiveBayes) - Constructor for class hex.naivebayes.NaiveBayesModel.NaiveBayesOutput

NaiveBayesParameters() - Constructor for class hex.naivebayes.NaiveBayesModel.NaiveBayesParameters

NaiveBayesParametersV3() - Constructor for class hex.schemas.NaiveBayesV3.NaiveBayesParametersV3

NaiveBayesV3 - Class in hex.schemas

NaiveBayesV3() - Constructor for class hex.schemas.NaiveBayesV3

NaiveBayesV3.NaiveBayesParametersV3 - Class in hex.schemas

names() - Method in class hex.glm.GLMModel

names - Variable in class hex.schemas.MakeGLMModelV3

nargs() - Method in class water.rapids.prims.AstPredictedVsActualByVar

nargs() - Method in class water.rapids.prims.AstSetCalibrationModel

nargs() - Method in class water.rapids.prims.isotonic.AstPoolAdjacentViolators

nargs() - Method in class water.rapids.prims.rulefit.AstPredictRule

nargs() - Method in class water.rapids.prims.tree.AstTreeUpdateWeights

nargs() - Method in class water.rapids.prims.word2vec.AstWord2VecToFrame

nas - Variable in class hex.schemas.TreeV3

NAsIncluded - Variable in class hex.rulefit.Condition

naSplitDir() - Method in class hex.tree.DTree.Split

nBins - Variable in class hex.DataInfo.Row

nbins - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3

nbins() - Method in class hex.tree.DHistogram

nbins_cats - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3

nbins_top_level - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3

NBSplinesTypeIDerivative - Class in hex.gam.GamSplines

NBSplinesTypeIDerivative(int, int, double[]) - Constructor for class hex.gam.GamSplines.NBSplinesTypeIDerivative

NBSplinesUtils - Class in hex.gam.GamSplines

NBSplinesUtils() - Constructor for class hex.gam.GamSplines.NBSplinesUtils

nclasses() - Method in class hex.coxph.CoxPHModel.CoxPHOutput

nclasses() - Method in class hex.ensemble.StackedEnsemble

nclasses() - Method in class hex.gam.GAMModel.GAMModelOutput

nclasses() - Method in class hex.glm.GLM

nclasses() - Method in class hex.glm.GLMModel.GLMOutput

nclasses() - Method in class hex.hglm.HGLMModel.HGLMModelOutput

nclasses() - Method in class hex.tree.gbm.GBMModel.GBMOutput

needsPostProcess() - Method in class hex.adaboost.AdaBoostModel

needsPostProcess() - Method in class hex.generic.GenericModel

needsPostProcess() - Method in class hex.glm.GLMModel

negative_weight - Variable in class hex.schemas.PSVMV3.PSVMParametersV3

nesterov_accelerated_gradient - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

The Nesterov accelerated gradient descent method is a modification to traditional gradient descent for convex functions.

Neurons - Class in hex.deeplearning

This class implements the concept of a Neuron layer in a Neural Network During training, every MRTask F/J thread is expected to create these neurons for every map call (Cheap to make).

Neurons.ExpRectifier - Class in hex.deeplearning

Neurons.ExpRectifierDropout - Class in hex.deeplearning

Exponential Rectifier with dropout

Neurons.Input - Class in hex.deeplearning

Input layer of the Neural Network This layer is different from other layers as it has no incoming weights, but instead gets its activation values from the training points.

Neurons.Linear - Class in hex.deeplearning

Output neurons for regression - Linear units

Neurons.Maxout - Class in hex.deeplearning

Maxout neurons (picks the max out of the k activation_j = sum(A_ij*x_i) + b_j) Requires k times the model parameters (weights/biases) as a "normal" neuron

Neurons.MaxoutDropout - Class in hex.deeplearning

Maxout neurons with dropout

Neurons.Output - Class in hex.deeplearning

Abstract class for Output neurons

Neurons.Rectifier - Class in hex.deeplearning

Rectifier linear unit (ReLU) neurons

Neurons.RectifierDropout - Class in hex.deeplearning

Rectifier linear unit (ReLU) neurons with dropout

Neurons.Softmax - Class in hex.deeplearning

Output neurons for classification - Softmax

Neurons.Tanh - Class in hex.deeplearning

Tanh neurons - most common, most stable

Neurons.TanhDropout - Class in hex.deeplearning

Tanh neurons with dropout

newDenseRow() - Method in class hex.DataInfo

newDenseRow(double[], long) - Method in class hex.DataInfo

newInstance() - Method in interface hex.ensemble.MetalearnerProvider

newParametersSchemaInstance() - Method in interface hex.ensemble.MetalearnerProvider

nextLevelConstraints(Constraints, int, double, SharedTreeModel.SharedTreeParameters) - Method in class hex.tree.DTree.Split

nextLevelHistos(DHistogram[], int, double, SharedTreeModel.SharedTreeParameters, Constraints, BranchInteractionConstraints) - Method in class hex.tree.DTree.Split

Prepare children histograms, one per column.

nextLevelInteractionConstraints(GlobalInteractionConstraints, int) - Method in class hex.tree.BranchInteractionConstraints

Decide which column indices is allowed to be used for the next split in the next level of a tree.

nextNumericIdx(int) - Method in class hex.DataInfo

Get the next expanded number-column index.

nfeatures() - Method in class hex.aggregator.AggregatorModel.AggregatorOutput

nfeatures() - Method in class hex.ensemble.StackedEnsembleModel.StackedEnsembleOutput

nfeatures() - Method in class hex.generic.GenericModelOutput

nfeatures() - Method in class hex.glrm.GLRM.Archetypes

nfeatures() - Method in class hex.glrm.GLRMModel.GLRMOutput

Override because base class implements ncols-1 for features with the last column as a response variable; for GLRM all the columns are features.

nfeatures() - Method in class hex.pca.PCAModel.PCAOutput

Override because base class implements ncols-1 for features with the last column as a response variable; for PCA all the columns are features.

nfeval() - Method in interface hex.optimization.OptimizationUtils.LineSearchSolver

nfeval() - Method in class hex.optimization.OptimizationUtils.MoreThuente

nfeval() - Method in class hex.optimization.OptimizationUtils.SimpleBacktrackingLS

nid() - Method in class hex.tree.DTree.Node

nid2Oob(int) - Static method in class hex.tree.ScoreBuildHistogram

nids0Index - Variable in class hex.tree.SharedTree.FrameMap

nlambdas - Variable in class hex.schemas.GAMV3.GAMParametersV3

nlambdas - Variable in class hex.schemas.GLMV3.GLMParametersV3

nlambdas - Variable in class hex.schemas.ModelSelectionV3.ModelSelectionParametersV3

nlearners - Variable in class hex.schemas.AdaBoostV3.AdaBoostParametersV3

nModelsInParallel(int) - Method in class hex.anovaglm.ANOVAGLM

nModelsInParallel(int) - Method in class hex.gam.GAM

nModelsInParallel(int) - Method in class hex.modelselection.ModelSelection

nModelsInParallel(int) - Method in class hex.tree.gbm.GBM

nNums - Variable in class hex.DataInfo.Row

NO_PARENT - Static variable in class hex.tree.DTree

nobs() - Method in class hex.glm.GLMTask.YMUTask

node(int) - Method in class hex.tree.DTree

Node(double[][], int, int) - Constructor for class hex.tree.isoforextended.isolationtree.IsolationTree.Node

node(double, double) - Method in class hex.tree.uplift.Divergence

Calculate distance metric between two probabilities in the node.

nomNA() - Method in class hex.tree.DHistogram

non_negative - Variable in class hex.schemas.ANOVAGLMV3.ANOVAGLMParametersV3

non_negative - Variable in class hex.schemas.GAMV3.GAMParametersV3

non_negative - Variable in class hex.schemas.GLMV3.GLMParametersV3

non_negative - Variable in class hex.schemas.ModelSelectionV3.ModelSelectionParametersV3

nonEmptyBins() - Method in class hex.tree.DHistogram

NonSPDMatrixException() - Constructor for exception hex.gram.Gram.NonSPDMatrixException

NonSPDMatrixException(String) - Constructor for exception hex.gram.Gram.NonSPDMatrixException

norm(double, double, double, double) - Method in class hex.tree.uplift.Divergence

Calculate normalization factor to normalize gain.

norm(double, double, double, double) - Method in class hex.tree.uplift.EuclideanDistance

norm(double, double, double, double) - Method in class hex.tree.uplift.KLDivergence

norm_model - Variable in class hex.schemas.Word2VecV3.Word2VecParametersV3

normalizeBeta(double[], boolean) - Method in class hex.DataInfo

normMul(int) - Method in class hex.DataInfo

normSub(int) - Method in class hex.DataInfo

notZeroLambdas(double[]) - Static method in class hex.glm.GLMUtils

nparallelism - Variable in class hex.schemas.ANOVAGLMV3.ANOVAGLMParametersV3

nparallelism - Variable in class hex.schemas.ModelSelectionV3.ModelSelectionParametersV3

npredictors() - Method in class hex.tree.drf.TreeMeasuresCollector.TreeMeasures

Returns number of voting predictors

nrows() - Method in class hex.tree.drf.TreeMeasuresCollector.TreeMeasures

Returns number of rows which were used during voting per individual tree.

nTreeEnsemblesInParallel(int) - Method in class hex.rulefit.RuleFit

ntrees - Variable in class hex.schemas.ExtendedIsolationForestV3.ExtendedIsolationForestParametersV3

ntrees - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3

ntrees() - Method in class hex.tree.CompressedForest

ntrees() - Method in class hex.tree.DTreeScorer

nullDOF() - Method in class hex.gam.MetricBuilderGAM

nullDOF() - Method in class hex.glm.GLMMetricBuilder

num_iteration_without_new_exemplar - Variable in class hex.schemas.AggregatorV99.AggregatorParametersV99

num_knots - Variable in class hex.schemas.GAMV3.GAMParametersV3

numCats() - Method in class hex.DataInfo

numcnt - Variable in class water.api.ModelMetricsGLRMV99

numColsExp(Frame, boolean) - Static method in class hex.util.LinearAlgebraUtils

Number of columns with categoricals expanded.

numControlNA() - Method in class hex.tree.DHistogram

NUMERICAL_FLAG - Static variable in class hex.tree.dt.mrtasks.CountBinsSamplesCountsMRTask

NUMERICAL_FLAG - Static variable in class hex.tree.dt.NumericFeatureLimits

NumericBin - Class in hex.tree.dt.binning

Single bin holding limits (min excluded), count of samples and count of class 0.

NumericBin(double, double, int, int) - Constructor for class hex.tree.dt.binning.NumericBin

NumericBin(double, double) - Constructor for class hex.tree.dt.binning.NumericBin

NumericBin(Pair<Double, Double>) - Constructor for class hex.tree.dt.binning.NumericBin

NumericFeatureLimits - Class in hex.tree.dt

Limits for one feature.

NumericFeatureLimits(double, double) - Constructor for class hex.tree.dt.NumericFeatureLimits

NumericSplittingRule - Class in hex.tree.dt

NumericSplittingRule(int, double, double) - Constructor for class hex.tree.dt.NumericSplittingRule

NumericSplittingRule(double) - Constructor for class hex.tree.dt.NumericSplittingRule

numerr - Variable in class water.api.ModelMetricsGLRMV99

numIds - Variable in class hex.DataInfo.Row

numNAFill() - Method in class hex.DataInfo

numNAFill(int) - Method in class hex.DataInfo

numNodes() - Method in class hex.tree.DTree.DecidedNode

numNodes() - Method in class hex.tree.DTree.LeafNode

numNodes() - Method in class hex.tree.DTree.Node

numNodes() - Method in class hex.tree.DTree.UndecidedNode

numNums() - Method in class hex.DataInfo

numStart() - Method in class hex.DataInfo

numTreatmentNA() - Method in class hex.tree.DHistogram

numTreshold - Variable in class hex.rulefit.Condition

numVals - Variable in class hex.DataInfo.Row

nv - Variable in class hex.schemas.SVDV99.SVDParametersV99

O

obj_reg - Variable in class hex.schemas.GAMV3.GAMParametersV3

obj_reg - Variable in class hex.schemas.GLMV3.GLMParametersV3

obj_reg - Variable in class hex.schemas.ModelSelectionV3.ModelSelectionParametersV3

objective - Variable in class hex.glm.ComputationState.GramGrad

objective() - Method in class hex.glm.ComputationState

objective(double[], double) - Method in class hex.glm.ComputationState

objective - Variable in class hex.schemas.GLRMModelV3.GLRMModelOutputV3

objective - Variable in class hex.schemas.PCAModelV3.PCAModelOutputV3

objective_epsilon - Variable in class hex.schemas.GAMV3.GAMParametersV3

objective_epsilon - Variable in class hex.schemas.GLMV3.GLMParametersV3

objective_epsilon - Variable in class hex.schemas.ModelSelectionV3.ModelSelectionParametersV3

offset - Variable in class hex.DataInfo.Row

offsetChunkId() - Method in class hex.DataInfo

offsetIdx() - Method in class hex.coxph.CoxPHModel.CoxPHOutput

offsetIndex - Variable in class hex.tree.SharedTree.FrameMap

offsets - Variable in class hex.schemas.GrepModelV3.GrepModelOutputV3

onCompletion(CountedCompleter) - Method in class hex.glm.GLM.GLMDriver

onCompletion(CountedCompleter) - Method in class hex.tree.SharedTree.ScoreBuildOneTree

oneHot(Frame, Model.InteractionSpec, boolean, boolean, boolean, boolean) - Static method in class hex.api.MakeGLMModelHandler

oneIndexOut(int, int) - Static method in class hex.anovaglm.ANOVAGLMUtils

oneSweepWSweepVector(ModelSelectionUtils.SweepVector[], double[][], int, int) - Static method in class hex.modelselection.ModelSelectionUtils

This method perform just one sweep of the sweeping action described in Step 3 of section V.II.IV of doc.

onExceptionalCompletion(Throwable, CountedCompleter) - Method in class hex.glm.GLM.GLMDriver

oob2Nid(int) - Static method in class hex.tree.ScoreBuildHistogram

oobtIndex - Variable in class hex.tree.SharedTree.FrameMap

operator - Variable in class hex.rulefit.Condition

OptimizationUtils - Class in hex.optimization

Created by tomasnykodym on 9/29/15.

OptimizationUtils() - Constructor for class hex.optimization.OptimizationUtils

OptimizationUtils.ExactLineSearch - Class in hex.optimization

This class implements the exact line search described in the doc, Algorithm 11.5

OptimizationUtils.GradientInfo - Class in hex.optimization

OptimizationUtils.GradientSolver - Interface in hex.optimization

Provides ginfo computation and line search evaluation specific to given problem.

OptimizationUtils.LineSearchSolver - Interface in hex.optimization

OptimizationUtils.MoreThuente - Class in hex.optimization

OptimizationUtils.SimpleBacktrackingLS - Class in hex.optimization

OUT_OF_BAG - Static variable in class hex.tree.ScoreBuildHistogram

Marker for sampled out rows

out_of_bounds - Variable in class hex.schemas.IsotonicRegressionV3.IsotonicRegressionParametersV3

OuterGramTask(Key<Job>, DataInfo) - Constructor for class hex.gram.Gram.OuterGramTask

output_frame - Variable in class hex.schemas.AggregatorModelV99.AggregatorModelOutputV99

outputChunkId() - Method in class hex.DataInfo

outputChunkId(int) - Method in class hex.DataInfo

overwrite_with_best_model - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

If enabled, store the best model under the destination key of this model at the end of training.

own_fields - Static variable in class hex.schemas.GrepV3.GrepParametersV3

P

p_values - Variable in class hex.schemas.GLMRegularizationPathV3

p_values_threshold - Variable in class hex.schemas.ModelSelectionV3.ModelSelectionParametersV3

parameters - Variable in class hex.deeplearning.DeepLearningModelInfo

params - Variable in class hex.deeplearning.Neurons

Parameters (deep-cloned() from the user input, can be modified here, e.g.

parentPred() - Method in class hex.tree.DTree.DecidedNode

Parms() - Constructor for class hex.psvm.psvm.PrimalDualIPM.Parms

Parms(double, double) - Constructor for class hex.psvm.psvm.PrimalDualIPM.Parms

path - Variable in class hex.schemas.GenericV3.GenericParametersV3

PCA - Class in hex.pca

Principal Components Analysis It computes the principal components from the singular value decomposition using the power method.

PCA(PCAModel.PCAParameters) - Constructor for class hex.pca.PCA

PCA(boolean) - Constructor for class hex.pca.PCA

pca_impl - Variable in class hex.schemas.PCAV3.PCAParametersV3

pca_method - Variable in class hex.schemas.AggregatorV99.AggregatorParametersV99

pca_method - Variable in class hex.schemas.PCAV3.PCAParametersV3

PCA_MTJ_EVD_DenseMatrix - Class in hex.pca.mtj

PCA_MTJ_EVD_DenseMatrix(double[][]) - Constructor for class hex.pca.mtj.PCA_MTJ_EVD_DenseMatrix

PCA_MTJ_EVD_SymmMatrix - Class in hex.pca.mtj

PCA_MTJ_EVD_SymmMatrix(double[][]) - Constructor for class hex.pca.mtj.PCA_MTJ_EVD_SymmMatrix

PCA_MTJ_SVD_DenseMatrix - Class in hex.pca.mtj

PCA_MTJ_SVD_DenseMatrix(double[][]) - Constructor for class hex.pca.mtj.PCA_MTJ_SVD_DenseMatrix

PCAImplementation - Enum in hex.pca

PCAInterface - Interface in hex.pca

PCAJama - Class in hex.pca.jama

PCAJama(double[][]) - Constructor for class hex.pca.jama.PCAJama

PCAModel - Class in hex.pca

PCAModel(Key, PCAModel.PCAParameters, PCAModel.PCAOutput) - Constructor for class hex.pca.PCAModel

PCAModel.PCAOutput - Class in hex.pca

PCAModel.PCAParameters - Class in hex.pca

PCAModel.PCAParameters.Method - Enum in hex.pca

PCAModelMetrics(int) - Constructor for class hex.pca.ModelMetricsPCA.PCAModelMetrics

PCAModelOutputV3() - Constructor for class hex.schemas.PCAModelV3.PCAModelOutputV3

PCAModelV3 - Class in hex.schemas

PCAModelV3() - Constructor for class hex.schemas.PCAModelV3

PCAModelV3.PCAModelOutputV3 - Class in hex.schemas

PCAMojoWriter - Class in hex.pca

PCAMojoWriter() - Constructor for class hex.pca.PCAMojoWriter

PCAMojoWriter(PCAModel) - Constructor for class hex.pca.PCAMojoWriter

PCAOutput(PCA) - Constructor for class hex.pca.PCAModel.PCAOutput

PCAParameters() - Constructor for class hex.pca.PCAModel.PCAParameters

PCAParametersV3() - Constructor for class hex.schemas.PCAV3.PCAParametersV3

PCAV3 - Class in hex.schemas

PCAV3() - Constructor for class hex.schemas.PCAV3

PCAV3.PCAParametersV3 - Class in hex.schemas

pcond - Variable in class hex.schemas.NaiveBayesModelV3.NaiveBayesModelOutputV3

performOneSweep(double[][], ModelSelectionUtils.SweepVector[], int, boolean) - Static method in class hex.modelselection.ModelSelectionUtils

Perform one sweep according to section II of doc and generate sweep vector according to section V.II of doc.

period - Variable in class hex.schemas.GLRMV3.GLRMParametersV3

perRow(double[], float[], Model) - Method in class hex.aggregator.ModelMetricsAggregator.AggregatorModelMetrics

perRow(double[], float[], double, double, Model) - Method in class hex.gam.MetricBuilderGAM

perRow(double[], float[], Model) - Method in class hex.gam.MetricBuilderGAM

perRow(double[], float[], Model) - Method in class hex.glm.GLMMetricBuilder

perRow(double[], float[], double, double, Model) - Method in class hex.glm.GLMMetricBuilder

perRow(double[], float[], Model) - Method in class hex.glrm.ModelMetricsGLRM.GlrmModelMetricsBuilder

perRow(double[], float[], double, double, double[], double[], double[][], int, Model) - Method in class hex.hglm.MetricBuilderHGLM

perRow(double[], float[], Model) - Method in class hex.hglm.MetricBuilderHGLM

perRow(double[], float[], Model) - Method in class hex.pca.ModelMetricsPCA.PCAModelMetrics

perRow(double[], float[], Model) - Method in class hex.psvm.MetricBuilderPSVM

perRow(double[], float[], double, double, Model) - Method in class hex.psvm.MetricBuilderPSVM

perRow(double[], float[], Model) - Method in class hex.svd.SVDModel.ModelMetricsSVD.SVDModelMetrics

perRow(double[], float[], double, double, Model) - Method in class hex.tree.isofor.MetricBuilderAnomalySupervised

perRow(double[], float[], Model) - Method in class hex.tree.isofor.ModelMetricsAnomaly.MetricBuilderAnomaly

pickBestModel(GLMModel.GLMParameters) - Method in class hex.glm.GLMModel.GLMOutput

pid() - Method in class hex.tree.DTree.Node

plain_language_rules - Variable in class hex.schemas.TreeV3

plug_values - Variable in class hex.schemas.ANOVAGLMV3.ANOVAGLMParametersV3

plug_values - Variable in class hex.schemas.GAMV3.GAMParametersV3

plug_values - Variable in class hex.schemas.GLMV3.GLMParametersV3

plug_values - Variable in class hex.schemas.HGLMV3.HGLMParametersV3

plug_values - Variable in class hex.schemas.ModelSelectionV3.ModelSelectionParametersV3

PlugValuesImputer(Frame) - Constructor for class hex.glm.GLM.PlugValuesImputer

PoolAdjacentViolatorsDriver - Class in hex.isotonic

Distributed implementation of Pool Adjacent Violators algorithm for H2O Frames

PoolAdjacentViolatorsDriver() - Constructor for class hex.isotonic.PoolAdjacentViolatorsDriver

positive_weight - Variable in class hex.schemas.PSVMV3.PSVMParametersV3

post(int, float, int) - Method in class hex.tree.TreeVisitor

postGlobal() - Method in class hex.ContributionsMeanAggregator

postGlobal() - Method in class hex.coxph.CoxPH.CoxPHTask

postGlobal() - Method in class hex.deeplearning.DeepLearningTask

After all reduces are done, the driver node calls this method to clean up This is only needed if we're not inside a DeepLearningTask2 (which will do the reduction between replicated data workers).

postGlobal() - Method in class hex.deeplearning.DeepLearningTask2

Finish up the work after all nodes have reduced their models via the above reduce() method.

postGlobal() - Method in class hex.gam.GamSplines.ThinPlateRegressionUtils.ScaleTPPenalty

postGlobal() - Method in class hex.gam.MatrixFrameUtils.GenCSSplineGamOneColumn

postGlobal() - Method in class hex.gam.MatrixFrameUtils.GenISplineGamOneColumn

postGlobal() - Method in class hex.gam.MatrixFrameUtils.GenMSplineGamOneColumn

postGlobal() - Method in class hex.glm.DispersionTask.ComputeMaxSumSeriesTsk

postGlobal() - Method in class hex.glm.GLMScore

postGlobal() - Method in class hex.glm.GLMTask.GLMMultinomialGradientBaseTask

postGlobal() - Method in class hex.glm.GLMTask.LSTask

postGlobal() - Method in class hex.glm.GLMTask.YMUTask

postGlobal() - Method in class hex.hglm.HGLMTask.ComputationEngineTask

postGlobal() - Method in class hex.tree.ExactSplitPoints

postGlobal() - Method in class hex.tree.Score

postGlobal() - Method in class hex.tree.ScoreBuildHistogram2

postProcessPredictions(Frame, Job, CalibrationHelper.OutputWithCalibration) - Static method in class hex.tree.CalibrationHelper

postProcessPredictions(Frame, Frame, Job) - Method in class hex.tree.SharedTreeModel

pre(int, float, IcedBitSet, int, int) - Method in class hex.tree.TreeVisitor

pre_split_se() - Method in class hex.tree.DTree.Split

pre_trained - Variable in class hex.schemas.Word2VecV3.Word2VecParametersV3

pred(int) - Method in class hex.tree.DTree.DecidedNode

pred() - Method in class hex.tree.DTree.LeafNode

pred_noise_bandwidth - Variable in class hex.schemas.GBMV3.GBMParametersV3

predCombo(String[], int[]) - Static method in class hex.anovaglm.ANOVAGLMUtils

predControl(int) - Method in class hex.tree.DTree.DecidedNode

predictions - Variable in class hex.schemas.TreeV3

predictorMeans() - Method in class hex.glm.GLMTask.YMUTask

predictors_bad - Variable in class hex.DataInfo.Row

predictorSDs() - Method in class hex.glm.GLMTask.YMUTask

predictRowStartingFromNode(double[], int, String) - Method in class hex.tree.dt.CompressedDT

Makes prediction by recursively evaluating the data through the tree.

predictRules(Frame, String[]) - Method in class hex.rulefit.RuleFitModel

predictScoreImpl(Frame, Frame, String, Job, boolean, CFuncRef) - Method in class hex.aggregator.AggregatorModel

predictScoreImpl(Frame, Frame, String, Job, boolean, CFuncRef) - Method in class hex.coxph.CoxPHModel

predictScoreImpl(Frame, Frame, String, Job, boolean, CFuncRef) - Method in class hex.deeplearning.DeepLearningModel

Make either a prediction or a reconstruction.

predictScoreImpl(Frame, Frame, String, Job, boolean, CFuncRef) - Method in class hex.ensemble.StackedEnsembleModel

For StackedEnsemble we call score on all the base_models and then combine the results with the metalearner to create the final predictions frame.

predictScoreImpl(Frame, Frame, String, Job, boolean, CFuncRef) - Method in class hex.gam.GAMModel

predictScoreImpl(Frame, Frame, String, Job, boolean, CFuncRef) - Method in class hex.generic.GenericModel

predictScoreImpl(Frame, Frame, String, Job, boolean, CFuncRef) - Method in class hex.glm.GLMModel

Score an already adapted frame.

predictScoreImpl(Frame, Frame, String, Job, boolean, CFuncRef) - Method in class hex.glrm.GLRMModel

predictScoreImpl(Frame, Frame, String, Job, boolean, CFuncRef) - Method in class hex.hglm.HGLMModel

predictScoreImpl(Frame, Frame, String, Job, boolean, CFuncRef) - Method in class hex.kmeans.KMeansModel

predictScoreImpl(Frame, Frame, String, Job, boolean, CFuncRef) - Method in class hex.pca.PCAModel

predictScoreImpl(Frame, Frame, String, Job, boolean, CFuncRef) - Method in class hex.svd.SVDModel

predTreatment(int) - Method in class hex.tree.DTree.DecidedNode

prepareGamVec(int, GAMModel.GAMParameters, Frame) - Static method in class hex.gam.MatrixFrameUtils.GamUtils

preSplitUpliftGain() - Method in class hex.tree.DTree.Split

pretrained_autoencoder - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

PrimalDualIPM - Class in hex.psvm.psvm

Implementation of Primal-Dual Interior Point Method based on https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/34638.pdf This implementation is based on and takes clues from the reference PSVM implementation in C++: https://code.google.com/archive/p/psvm/source/default/source original code: Copyright 2007 Google Inc., Apache License, Version 2.0

PrimalDualIPM() - Constructor for class hex.psvm.psvm.PrimalDualIPM

PrimalDualIPM.Parms - Class in hex.psvm.psvm

PrimalDualIPM.ProgressObserver - Interface in hex.psvm.psvm

printConstraintSummary(GLMModel, ComputationState, String[]) - Static method in class hex.glm.ConstrainedGLMUtils

printConstraintSummary(ComputationState, String[]) - Static method in class hex.glm.ConstrainedGLMUtils

prior - Variable in class hex.schemas.ANOVAGLMV3.ANOVAGLMParametersV3

prior - Variable in class hex.schemas.GAMV3.GAMParametersV3

prior - Variable in class hex.schemas.GLMV3.GLMParametersV3

prior - Variable in class hex.schemas.ModelSelectionV3.ModelSelectionParametersV3

probability - Variable in class hex.tree.dt.DTPrediction

process(ModelSelectionUtils.SweepElement, List<ModelSelectionUtils.SweepElement>) - Static method in class hex.modelselection.ModelSelectionUtils

This method will generate all the elements that are needed to perform sweeping on the currEle.

processMiniBatch(long, double[], double[], int) - Method in class hex.deeplearning.DeepLearningTask

Apply the gradient to update the weights

processMiniBatch(long, double[], double[], int) - Method in class hex.FrameTask

Mini-Batch update of model parameters

processRow(DataInfo.Row) - Method in class hex.coxph.CoxPH.CoxPHTask

processRow(long, DataInfo.Row, int) - Method in class hex.deeplearning.DeepLearningTask

Process one training row at a time (online learning)

processRow(long, DataInfo.Row) - Method in class hex.FrameTask

Method to process one row of the data.

processRow(long, DataInfo.Row, NewChunk[]) - Method in class hex.FrameTask

processRow(long, DataInfo.Row, int) - Method in class hex.FrameTask

processRow(DataInfo.Row) - Method in class hex.FrameTask2

processRow(DataInfo.Row) - Method in class hex.glm.GLMTask.ComputeDiTriGammaTsk

processRow(DataInfo.Row) - Method in class hex.glm.GLMTask.ComputeGammaMLSETsk

processRow(DataInfo.Row) - Method in class hex.glm.GLMTask.ComputeSEorDEVIANCETsk

processRow(DataInfo.Row) - Method in class hex.glm.GLMTask.GLMIterationTask

processRow(DataInfo.Row) - Method in class hex.glm.GLMTask.GLMIterationTaskMultinomial

processRow(DataInfo.Row) - Method in class hex.glm.GLMTask.GLMMultinomialUpdate

processRow(DataInfo.Row) - Method in class hex.glm.GLMTask.GLMMultinomialWLSTask

processRow(DataInfo.Row) - Method in class hex.glm.GLMTask.GLMWLSTask

processRow(DataInfo.Row) - Method in class hex.glm.GLMTask.LSTask

processRow(DataInfo.Row) - Method in class hex.gram.Gram.GramTask

processRow(long, DataInfo.Row, NewChunk[]) - Method in class hex.util.LinearAlgebraUtils.BMulTask

productMtDM(Frame, Vec) - Static method in class hex.psvm.psvm.MatrixUtils

Calculates matrix product M'DM

productMtv(Frame, Vec) - Static method in class hex.psvm.psvm.MatrixUtils

Calculates matrix-vector product M'v

progress(double[], OptimizationUtils.GradientInfo) - Method in class hex.glm.GLM.GLMDriver

progress(double[], double) - Method in class hex.glm.GLM.GLMDriver

progress(double[], OptimizationUtils.GradientInfo) - Method in interface hex.optimization.L_BFGS.ProgressMonitor

progressUnits() - Method in class hex.adaboost.AdaBoostModel.AdaBoostParameters

progressUnits() - Method in class hex.aggregator.AggregatorModel.AggregatorParameters

progressUnits() - Method in class hex.anovaglm.ANOVAGLMModel.ANOVAGLMParameters

progressUnits() - Method in class hex.coxph.CoxPHModel.CoxPHParameters

progressUnits() - Method in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

progressUnits() - Method in class hex.ensemble.StackedEnsembleModel.StackedEnsembleParameters

progressUnits() - Method in class hex.gam.GAMModel.GAMParameters

progressUnits() - Method in class hex.generic.GenericModelParameters

progressUnits() - Method in class hex.glm.GLMModel.GLMParameters

progressUnits() - Method in class hex.glrm.GLRMModel.GLRMParameters

progressUnits() - Method in class hex.grep.GrepModel.GrepParameters

progressUnits() - Method in class hex.hglm.HGLMModel.HGLMParameters

progressUnits() - Method in class hex.isotonic.IsotonicRegressionModel.IsotonicRegressionParameters

progressUnits() - Method in class hex.kmeans.KMeansModel.KMeansParameters

progressUnits() - Method in class hex.modelselection.ModelSelectionModel.ModelSelectionParameters

progressUnits() - Method in class hex.naivebayes.NaiveBayesModel.NaiveBayesParameters

progressUnits() - Method in class hex.pca.PCAModel.PCAParameters

progressUnits() - Method in class hex.psvm.PSVMModel.PSVMParameters

progressUnits() - Method in class hex.rulefit.RuleFitModel.RuleFitParameters

progressUnits() - Method in class hex.svd.SVDModel.SVDParameters

progressUnits() - Method in class hex.tree.dt.DTModel.DTParameters

progressUnits() - Method in class hex.tree.isoforextended.ExtendedIsolationForestModel.ExtendedIsolationForestParameters

progressUnits() - Method in class hex.tree.SharedTreeModel.SharedTreeParameters

progressUnits() - Method in class hex.tree.uplift.UpliftDRFModel.UpliftDRFParameters

progressUnits() - Method in class hex.word2vec.Word2VecModel.Word2VecParameters

providesVarImp() - Method in class hex.tree.SharedTree

proximal_gradient(double[], double, double[], double[], double[]) - Static method in class hex.glm.GLM.ProximalGradientSolver

ProximalGradientInfo(OptimizationUtils.GradientInfo, double, double[]) - Constructor for class hex.glm.GLM.ProximalGradientInfo

ProximalGradientSolver(OptimizationUtils.GradientSolver, double[], double[], double, double, OptimizationUtils.GradientInfo, L_BFGS.ProgressMonitor) - Constructor for class hex.glm.GLM.ProximalGradientSolver

PSVM - Class in hex.psvm

PSVM(boolean) - Constructor for class hex.psvm.PSVM

PSVM(PSVMModel.PSVMParameters) - Constructor for class hex.psvm.PSVM

PSVMModel - Class in hex.psvm

PSVMModel(Key<PSVMModel>, PSVMModel.PSVMParameters, PSVMModel.PSVMModelOutput) - Constructor for class hex.psvm.PSVMModel

PSVMModel.PSVMModelOutput - Class in hex.psvm

PSVMModel.PSVMParameters - Class in hex.psvm

PSVMModelOutputV3() - Constructor for class hex.schemas.PSVMModelV3.PSVMModelOutputV3

PSVMModelV3 - Class in hex.schemas

PSVMModelV3() - Constructor for class hex.schemas.PSVMModelV3

PSVMModelV3.PSVMModelOutputV3 - Class in hex.schemas

PSVMParameters() - Constructor for class hex.psvm.PSVMModel.PSVMParameters

PSVMParametersV3() - Constructor for class hex.schemas.PSVMV3.PSVMParametersV3

PSVMV3 - Class in hex.schemas

PSVMV3() - Constructor for class hex.schemas.PSVMV3

PSVMV3.PSVMParametersV3 - Class in hex.schemas

pValues() - Method in class hex.glm.GLMModel.GLMOutput

pValues(long) - Method in class hex.glm.GLMModel.Submodel

pValues(double[], long) - Method in class hex.glm.GLMModel.Submodel

Q

qrCholesky(List<Integer>, double[][], boolean) - Method in class hex.glm.ComputationState.GramGrad

qrCholesky(ArrayList<Integer>, boolean) - Method in class hex.gram.Gram

Compute Cholesky decompostion by computing partial QR decomposition (R == LU).

quiet_mode - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

Enable quiet mode for less output to standard output.

R

r2_stopping - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3

raiseReproducibilityWarning(String, int) - Method in class hex.tree.gbm.GBM

rand_family - Variable in class hex.schemas.HGLMV3.HGLMParametersV3

random_coefficient_names - Variable in class hex.schemas.HGLMModelV3.HGLMModelOutputV3

random_columns - Variable in class hex.schemas.HGLMV3.HGLMParametersV3

random_intercept - Variable in class hex.schemas.HGLMV3.HGLMParametersV3

randomlySparsifyActivation(Storage.Vector, long) - Method in class hex.deeplearning.Dropout

rank() - Method in class hex.glm.GLMModel.GLMOutput

rank() - Method in class hex.glm.GLMModel.Submodel

rank() - Method in class hex.glrm.GLRM.Archetypes

rank_ratio - Variable in class hex.schemas.PSVMV3.PSVMParametersV3

rate(double) - Method in class hex.deeplearning.Neurons

The learning rate

rate - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

When adaptive learning rate is disabled, the magnitude of the weight updates are determined by the user specified learning rate (potentially annealed), and are a function of the difference between the predicted value and the target value.

rate_annealing - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

Learning rate annealing reduces the learning rate to "freeze" into local minima in the optimization landscape.

rate_decay - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

The learning rate decay parameter controls the change of learning rate across layers.

raw() - Method in class hex.coxph.Storage.DenseRowMatrix

raw() - Method in interface hex.coxph.Storage.Matrix

raw() - Method in class hex.deeplearning.Storage.DenseColMatrix

raw() - Method in class hex.deeplearning.Storage.DenseRowMatrix

raw() - Method in class hex.deeplearning.Storage.DenseVector

raw() - Method in interface hex.deeplearning.Storage.Matrix

raw() - Method in class hex.deeplearning.Storage.SparseRowMatrix

raw() - Method in interface hex.deeplearning.Storage.Tensor

raw() - Method in interface hex.deeplearning.Storage.Vector

read_impl(AutoBuffer) - Method in class hex.coxph.CoxPHModel.FrameMatrix

read_impl(AutoBuffer) - Method in class hex.word2vec.WordCountTask

readAll_impl(AutoBuffer, Futures) - Method in class hex.adaboost.AdaBoostModel

readAll_impl(AutoBuffer, Futures) - Method in class hex.anovaglm.ANOVAGLMModel

readAll_impl(AutoBuffer, Futures) - Method in class hex.ensemble.StackedEnsembleModel

Read in models (base + metalearner)

readAll_impl(AutoBuffer, Futures) - Method in class hex.gam.GAMModel

readAll_impl(AutoBuffer, Futures) - Method in class hex.glm.GLMModel

readAll_impl(AutoBuffer, Futures) - Method in class hex.glrm.GLRMModel

readAll_impl(AutoBuffer, Futures) - Method in class hex.hglm.HGLMModel

readAll_impl(AutoBuffer, Futures) - Method in class hex.modelselection.ModelSelectionModel

readAll_impl(AutoBuffer, Futures) - Method in class hex.svd.SVDModel

readAll_impl(AutoBuffer, Futures) - Method in class hex.tree.dt.DTModel

readAll_impl(AutoBuffer, Futures) - Method in class hex.tree.isoforextended.ExtendedIsolationForestModel

readAll_impl(AutoBuffer, Futures) - Method in class hex.tree.SharedTreeModel

rebalance(Frame, boolean, String) - Method in class hex.deeplearning.DeepLearning

ReconstructTreeState - Class in hex.tree

Computing oob scores over all trees and rows and reconstructing ntree_id, oobt fields in given frame.

ReconstructTreeState(int, int, SharedTree, double, CompressedForest, boolean) - Constructor for class hex.tree.ReconstructTreeState

recover_svd - Variable in class hex.schemas.GLRMV3.GLRMParametersV3

Rectifier(int) - Constructor for class hex.deeplearning.Neurons.Rectifier

RectifierDropout(int) - Constructor for class hex.deeplearning.Neurons.RectifierDropout

reduce(ContributionsMeanAggregator) - Method in class hex.ContributionsMeanAggregator

reduce(CoxPH.CoxPHTask) - Method in class hex.coxph.CoxPH.CoxPHTask

reduce(DeepLearningTask) - Method in class hex.deeplearning.DeepLearningTask

Average the per-node models (for elastic averaging, already wrote them to DKV in postLocal()) This is a no-op between F/J worker threads (operate on the same weights/biases)

reduce(DeepLearningTask2) - Method in class hex.deeplearning.DeepLearningTask2

Reduce between worker nodes, with network traffic (if greater than 1 nodes) After all reduce()'s are done, postGlobal() will be called

reduce(FrameTask.ExtractDenseRow) - Method in class hex.FrameTask.ExtractDenseRow

reduce(ThinPlateRegressionUtils.ScaleTPPenalty) - Method in class hex.gam.GamSplines.ThinPlateRegressionUtils.ScaleTPPenalty

reduce(GenCSSplineGamOneColumn) - Method in class hex.gam.MatrixFrameUtils.GenCSSplineGamOneColumn

reduce(GenISplineGamOneColumn) - Method in class hex.gam.MatrixFrameUtils.GenISplineGamOneColumn

reduce(GenMSplineGamOneColumn) - Method in class hex.gam.MatrixFrameUtils.GenMSplineGamOneColumn

reduce(MetricBuilderGAM) - Method in class hex.gam.MetricBuilderGAM

reduce(DispersionTask.ComputeMaxSumSeriesTsk) - Method in class hex.glm.DispersionTask.ComputeMaxSumSeriesTsk

reduce(GLMMetricBuilder) - Method in class hex.glm.GLMMetricBuilder

reduce(GLMScore) - Method in class hex.glm.GLMScore

reduce(GLMTask.ComputeDiTriGammaTsk) - Method in class hex.glm.GLMTask.ComputeDiTriGammaTsk

reduce(GLMTask.ComputeGammaMLSETsk) - Method in class hex.glm.GLMTask.ComputeGammaMLSETsk

reduce(GLMTask.ComputeSEorDEVIANCETsk) - Method in class hex.glm.GLMTask.ComputeSEorDEVIANCETsk

reduce(GLMTask.GLMCoordinateDescentTaskSeqIntercept) - Method in class hex.glm.GLMTask.GLMCoordinateDescentTaskSeqIntercept

reduce(GLMTask.GLMCoordinateDescentTaskSeqNaive) - Method in class hex.glm.GLMTask.GLMCoordinateDescentTaskSeqNaive

reduce(GLMTask.GLMGenerateWeightsTask) - Method in class hex.glm.GLMTask.GLMGenerateWeightsTask

reduce(GLMTask.GLMIterationTask) - Method in class hex.glm.GLMTask.GLMIterationTask

reduce(GLMTask.GLMIterationTaskMultinomial) - Method in class hex.glm.GLMTask.GLMIterationTaskMultinomial

reduce(GLMTask.GLMMultinomialGradientBaseTask) - Method in class hex.glm.GLMTask.GLMMultinomialGradientBaseTask

reduce(GLMTask.LSTask) - Method in class hex.glm.GLMTask.LSTask

reduce(GLMTask.YMUTask) - Method in class hex.glm.GLMTask.YMUTask

reduce(TweedieEstimator) - Method in class hex.glm.TweedieEstimator

reduce(ModelMetricsGLRM.GlrmModelMetricsBuilder) - Method in class hex.glrm.ModelMetricsGLRM.GlrmModelMetricsBuilder

reduce(Gram.GramTask) - Method in class hex.gram.Gram.GramTask

reduce(Gram.OuterGramTask) - Method in class hex.gram.Gram.OuterGramTask

reduce(HGLMScore) - Method in class hex.hglm.HGLMScore

reduce(HGLMTask.ComputationEngineTask) - Method in class hex.hglm.HGLMTask.ComputationEngineTask

reduce(HGLMTask.ResidualLLHTask) - Method in class hex.hglm.HGLMTask.ResidualLLHTask

reduce(MetricBuilderHGLM) - Method in class hex.hglm.MetricBuilderHGLM

reduce(T) - Method in class hex.psvm.MetricBuilderPSVM

reduce(TreeMeasuresCollector) - Method in class hex.tree.drf.TreeMeasuresCollector

reduce(CountBinsSamplesCountsMRTask) - Method in class hex.tree.dt.mrtasks.CountBinsSamplesCountsMRTask

reduce(FeaturesLimitsMRTask) - Method in class hex.tree.dt.mrtasks.FeaturesLimitsMRTask

reduce(GetClassCountsMRTask) - Method in class hex.tree.dt.mrtasks.GetClassCountsMRTask

reduce(ScoreDTTask) - Method in class hex.tree.dt.mrtasks.ScoreDTTask

reduce(ExactSplitPoints) - Method in class hex.tree.ExactSplitPoints

reduce(ModelMetricsAnomaly.MetricBuilderAnomaly) - Method in class hex.tree.isofor.ModelMetricsAnomaly.MetricBuilderAnomaly

reduce(Score) - Method in class hex.tree.Score

reduce(ScoreBuildHistogram) - Method in class hex.tree.ScoreBuildHistogram

reduce(LinearAlgebraUtils.FindMaxIndex) - Method in class hex.util.LinearAlgebraUtils.FindMaxIndex

reduce(LinearAlgebraUtils.SMulTask) - Method in class hex.util.LinearAlgebraUtils.SMulTask

reduce(WordCountTask) - Method in class hex.word2vec.WordCountTask

reduce(WordVectorConverter) - Method in class hex.word2vec.WordVectorConverter

reduce(WordVectorTrainer) - Method in class hex.word2vec.WordVectorTrainer

reducePrecision() - Method in class hex.tree.DHistogram

Cast bin values (except for sums of weights) to floats to drop least significant bits.

regex - Variable in class hex.schemas.GrepV3.GrepParametersV3

RegisterAlgos - Class in hex.api

RegisterAlgos() - Constructor for class hex.api.RegisterAlgos

registerEndPoints(RestApiContext) - Method in class hex.api.RegisterAlgos

regression_stop - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

The stopping criteria in terms of regression error (MSE) on the training data scoring dataset.

RegressionInfluenceDiagBinomial(Job, double[], double[][], GLMModel.GLMParameters, DataInfo, double[]) - Constructor for class hex.glm.RegressionInfluenceDiagnosticsTasks.RegressionInfluenceDiagBinomial

RegressionInfluenceDiagGaussian(double[][], double[], Job) - Constructor for class hex.glm.RegressionInfluenceDiagnosticsTasks.RegressionInfluenceDiagGaussian

RegressionInfluenceDiagnosticsTasks - Class in hex.glm

Classes defined here implemented the various pieces of regression influence diagnostics described in this doc: https://github.com/h2oai/h2o-3/issues/7044.

RegressionInfluenceDiagnosticsTasks() - Constructor for class hex.glm.RegressionInfluenceDiagnosticsTasks

RegressionInfluenceDiagnosticsTasks.ComputeNewBetaVarEstimatedGaussian - Class in hex.glm

RegressionInfluenceDiagnosticsTasks.RegressionInfluenceDiagBinomial - Class in hex.glm

RegressionInfluenceDiagnosticsTasks.RegressionInfluenceDiagGaussian - Class in hex.glm

generate DFBETAS as in equation 4 of the document.

regularization_x - Variable in class hex.schemas.GLRMV3.GLRMParametersV3

regularization_y - Variable in class hex.schemas.GLRMV3.GLRMParametersV3

RegularizationPath() - Constructor for class hex.glm.GLMModel.RegularizationPath

rel_improvement - Variable in class hex.optimization.L_BFGS.Result

rel_tol_num_exemplars - Variable in class hex.schemas.AggregatorV99.AggregatorParametersV99

remove_collinear_columns - Variable in class hex.schemas.GAMV3.GAMParametersV3

remove_collinear_columns - Variable in class hex.schemas.GLMV3.GLMParametersV3

remove_collinear_columns - Variable in class hex.schemas.ModelSelectionV3.ModelSelectionParametersV3

remove_duplicates - Variable in class hex.schemas.RuleFitV3.RuleFitParametersV3

remove_impl(Futures, boolean) - Method in class hex.adaboost.AdaBoostModel

remove_impl(Futures, boolean) - Method in class hex.aggregator.AggregatorModel

remove_impl(Futures, boolean) - Method in class hex.anovaglm.ANOVAGLMModel

remove_impl(Futures, boolean) - Method in class hex.coxph.CoxPHModel

remove_impl(Futures, boolean) - Method in class hex.deeplearning.DeepLearningModel

remove_impl(Futures, boolean) - Method in class hex.ensemble.StackedEnsembleModel

remove_impl(Futures, boolean) - Method in class hex.gam.GAMModel

remove_impl(Futures, boolean) - Method in class hex.generic.GenericModel

remove_impl(Futures, boolean) - Method in class hex.glm.GLMModel

remove_impl(Futures, boolean) - Method in class hex.glrm.GLRMModel

remove_impl(Futures, boolean) - Method in class hex.hglm.HGLMModel

remove_impl(Futures, boolean) - Method in class hex.modelselection.ModelSelectionModel

remove_impl(Futures, boolean) - Method in class hex.psvm.PSVMModel

remove_impl(Futures, boolean) - Method in class hex.rulefit.RuleFitModel

remove_impl(Futures, boolean) - Method in class hex.svd.SVDModel

remove_impl(Futures, boolean) - Method in class hex.tree.dt.DTModel

remove_impl(Futures, boolean) - Method in class hex.tree.isoforextended.ExtendedIsolationForestModel

remove_impl(Futures, boolean) - Method in class hex.tree.SharedTreeModel

removeCenteringIS(double[][][], GAMModel.GAMParameters) - Static method in class hex.gam.MatrixFrameUtils.GamUtils

This function is used to remove the dimension change due to centering for I-splines

removeCols(int[]) - Method in class hex.glm.ComputationState

removeFromDKV(Frame[], int) - Static method in class hex.anovaglm.ANOVAGLMUtils

removePredictors(GLMModel.GLMParameters, Frame) - Static method in class hex.glm.GLMUtils

removeRedCols(double[], double[], double[]) - Static method in class hex.glm.GLMUtils

removeSpecialColumns(Frame) - Method in class hex.tree.SharedTreeModelWithContributions

removeSpecialNNonNumericColumns(Frame) - Method in class hex.tree.SharedTreeModelWithContributions

removeTrainingFrames(Frame[]) - Static method in class hex.modelselection.ModelSelectionUtils

replacement(List<Integer>, List<Integer>, Set<BitSet>, BitSet, ModelSelection.SweepModel, int[][]) - Method in class hex.modelselection.ModelSelection

consider the predictors in subset as pred0, pred1, pred2 (using subset size 3 as example): a.

replacement(List<Integer>, List<String>, double, ModelSelectionModel.ModelSelectionParameters, int, String, List<Integer>, Model.Parameters.FoldAssignmentScheme, Set<BitSet>) - Static method in class hex.modelselection.ModelSelection

consider the predictors in subset as pred0, pred1, pred2 (using subset size 3 as example): a.

replicate_training_data - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

Replicate the entire training dataset onto every node for faster training on small datasets.

reportProgress(int, double, double, double, boolean) - Method in interface hex.psvm.psvm.PrimalDualIPM.ProgressObserver

representation_name - Variable in class hex.schemas.GLRMModelV3.GLRMModelOutputV3

representation_name - Variable in class hex.schemas.GLRMV3.GLRMParametersV3

reproducible - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

resDOF() - Method in class hex.gam.MetricBuilderGAM

resDOF() - Method in class hex.glm.GLMMetricBuilder

reset(double[], ComputationState, List<String>) - Method in class hex.optimization.OptimizationUtils.ExactLineSearch

resetCatPredNames(DataInfo, int[], List<String>) - Method in class hex.modelselection.ModelSelectionModel.ModelSelectionModelOutput

resetNumPredNames(List<String>, List<String>) - Method in class hex.modelselection.ModelSelectionModel.ModelSelectionModelOutput

reshape1DArray(double[], int, int) - Static method in class hex.util.LinearAlgebraUtils

residualDeviance() - Method in class hex.gam.MetricBuilderGAM

residualDeviance() - Method in class hex.glm.GLMMetricBuilder

ResidualLLHTask(Job, HGLMModel.HGLMParameters, DataInfo, double[][], double[], HGLMTask.ComputationEngineTask) - Constructor for class hex.hglm.HGLMTask.ResidualLLHTask

resizeConstraintInfo(ConstrainedGLMUtils.LinearConstraints[], ConstrainedGLMUtils.LinearConstraints[]) - Method in class hex.glm.ComputationState

respControlNA() - Method in class hex.tree.DHistogram

RESPIND - Static variable in class hex.glm.DispersionTask

response - Variable in class hex.DataInfo.Row

response(int) - Method in class hex.DataInfo.Row

response_bad - Variable in class hex.DataInfo.Row

responseChunkId(int) - Method in class hex.DataInfo

responseColumn - Variable in class hex.ensemble.StackedEnsembleModel

responseIdx() - Method in class hex.tree.isofor.IsolationForestModel.IsolationForestOutput

responseIndex - Variable in class hex.tree.SharedTree.FrameMap

responseMeans() - Method in class hex.glm.GLMTask.YMUTask

responseName() - Method in class hex.tree.isofor.IsolationForestModel.IsolationForestOutput

responseSDs() - Method in class hex.glm.GLMTask.YMUTask

respTreatmentNA() - Method in class hex.tree.DHistogram

result() - Method in class hex.anovaglm.ANOVAGLMModel

Return the ANOVA table as an H2OFrame per seb suggestion

result() - Method in class hex.modelselection.ModelSelectionModel

Result(boolean, int, double[], OptimizationUtils.GradientInfo, double) - Constructor for class hex.optimization.L_BFGS.Result

result - Variable in class hex.schemas.DataInfoFrameV3

resultSSE() - Method in class hex.tree.drf.TreeMeasuresCollector

resultVotes() - Method in class hex.tree.drf.TreeMeasuresCollector

resumeFromCheckpoint(SharedTree) - Method in class hex.tree.SharedTree.Driver

Restore the workspace from a previous model (checkpoint)

revertCoeffNames(String[], int, TwoDimTableV3) - Method in class hex.schemas.GLMModelV3.GLMModelOutputV3

rho() - Method in class hex.glm.GLM.GramSolver

rho() - Method in class hex.glm.GLM.ProximalGradientSolver

rho() - Method in interface hex.optimization.ADMM.ProximalSolver

rho - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

The first of two hyper parameters for adaptive learning rate (ADADELTA).

rho - Variable in class hex.schemas.PSVMModelV3.PSVMModelOutputV3

rid - Variable in class hex.DataInfo.Row

right_children - Variable in class hex.schemas.TreeV3

rms_weight - Variable in class hex.deeplearning.DeepLearningModelInfo

rngForChunk(int) - Method in class hex.tree.CompressedTree

root() - Method in class hex.tree.DTree

root_node_id - Variable in class hex.schemas.TreeV3

ROUND_ROBIN_CANDIDATES - Static variable in enum hex.tree.SharedTreeModel.SharedTreeParameters.HistogramType

routeSample(double[]) - Method in class hex.tree.dt.AbstractSplittingRule

routeSample(double[]) - Method in class hex.tree.dt.CategoricalSplittingRule

routeSample(double[]) - Method in class hex.tree.dt.NumericSplittingRule

Row(boolean, int, int, int, int, long) - Constructor for class hex.DataInfo.Row

Row(boolean, double[], int[], double[], int, long) - Constructor for class hex.DataInfo.Row

Row(double[]) - Constructor for class hex.DataInfo.Row

row(int) - Method in class hex.DataInfo.Rows

rows() - Method in class hex.coxph.Storage.DenseRowMatrix

rows() - Method in interface hex.coxph.Storage.Matrix

rows(Chunk[]) - Method in class hex.DataInfo

rows(Chunk[], boolean) - Method in class hex.DataInfo

rows() - Method in class hex.deeplearning.Storage.DenseColMatrix

rows() - Method in class hex.deeplearning.Storage.DenseRowMatrix

rows() - Method in interface hex.deeplearning.Storage.Matrix

rows() - Method in class hex.deeplearning.Storage.SparseRowMatrix

rows() - Method in interface hex.deeplearning.Storage.Tensor

rowToTreeAssignment(Frame, Key<Frame>, Job<Frame>) - Method in class hex.tree.gbm.GBMModel

Rule - Class in hex.rulefit

Rule(Condition[], double, String) - Constructor for class hex.rulefit.Rule

Rule(Condition[], double, String, double, double) - Constructor for class hex.rulefit.Rule

rule_generation_ntrees - Variable in class hex.schemas.RuleFitV3.RuleFitParametersV3

rule_importance - Variable in class hex.schemas.RuleFitModelV3.RuleFitModelOutputV3

RuleEnsemble - Class in hex.rulefit

RuleEnsemble(Rule[]) - Constructor for class hex.rulefit.RuleEnsemble

ruleExplanation - Variable in class hex.tree.dt.DTPrediction

RuleFit - Class in hex.rulefit

Rule Fit
http://statweb.stanford.edu/~jhf/ftp/RuleFit.pdf https://github.com/h2oai/h2o-tutorials/blob/8df6b492afa172095e2595922f0b67f8d715d1e0/best-practices/explainable-models/rulefit.py

RuleFit(RuleFitModel.RuleFitParameters) - Constructor for class hex.rulefit.RuleFit

RuleFit(boolean) - Constructor for class hex.rulefit.RuleFit

RuleFitModel - Class in hex.rulefit

RuleFitModel(Key<RuleFitModel>, RuleFitModel.RuleFitParameters, RuleFitModel.RuleFitOutput, GLMModel, RuleEnsemble) - Constructor for class hex.rulefit.RuleFitModel

RuleFitModel.Algorithm - Enum in hex.rulefit

RuleFitModel.ModelType - Enum in hex.rulefit

RuleFitModel.RuleFitOutput - Class in hex.rulefit

RuleFitModel.RuleFitParameters - Class in hex.rulefit

RuleFitModelOutputV3() - Constructor for class hex.schemas.RuleFitModelV3.RuleFitModelOutputV3

RuleFitModelV3 - Class in hex.schemas

RuleFitModelV3() - Constructor for class hex.schemas.RuleFitModelV3

RuleFitModelV3.RuleFitModelOutputV3 - Class in hex.schemas

RuleFitMojoWriter - Class in hex.rulefit

RuleFitMojoWriter() - Constructor for class hex.rulefit.RuleFitMojoWriter

RuleFitMojoWriter(RuleFitModel) - Constructor for class hex.rulefit.RuleFitMojoWriter

RuleFitOutput(RuleFit) - Constructor for class hex.rulefit.RuleFitModel.RuleFitOutput

RuleFitParameters() - Constructor for class hex.rulefit.RuleFitModel.RuleFitParameters

RuleFitParametersV3() - Constructor for class hex.schemas.RuleFitV3.RuleFitParametersV3

RuleFitUtils - Class in hex.rulefit

RuleFitUtils() - Constructor for class hex.rulefit.RuleFitUtils

RuleFitV3 - Class in hex.schemas

RuleFitV3() - Constructor for class hex.schemas.RuleFitV3

RuleFitV3.RuleFitParametersV3 - Class in hex.schemas

runAndGetOutput(Job, Key<Frame>, String[]) - Method in class hex.ContributionsWithBackgroundFrameTask

runPAV(Frame) - Static method in class hex.isotonic.PoolAdjacentViolatorsDriver

S

Sample - Class in hex.tree

Sample(DTree, double, double[]) - Constructor for class hex.tree.Sample

Sample(long, double, double[], int, int) - Constructor for class hex.tree.Sample

sample_rate - Variable in class hex.schemas.DRFV3.DRFParametersV3

sample_rate - Variable in class hex.schemas.GBMV3.GBMParametersV3

sample_rate - Variable in class hex.schemas.IsolationForestV3.IsolationForestParametersV3

sample_rate - Variable in class hex.schemas.UpliftDRFV3.UpliftDRFParametersV3

sample_rate_per_class - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3

sample_size - Variable in class hex.schemas.ExtendedIsolationForestV3.ExtendedIsolationForestParametersV3

sample_size - Variable in class hex.schemas.IsolationForestV3.IsolationForestParametersV3

save_mapping_frame - Variable in class hex.schemas.AggregatorV99.AggregatorParametersV99

save_transformed_framekeys - Variable in class hex.schemas.ANOVAGLMV3.ANOVAGLMParametersV3

scale - Variable in class hex.schemas.GAMV3.GAMParametersV3

scale_tp_penalty_mat - Variable in class hex.schemas.GAMV3.GAMParametersV3

ScaleTPPenalty(double[][], Frame) - Constructor for class hex.gam.GamSplines.ThinPlateRegressionUtils.ScaleTPPenalty

schema() - Method in class hex.coxph.CoxPHModel

schema() - Method in class hex.naivebayes.NaiveBayesModel

score(Frame, String, Job, boolean, CFuncRef) - Method in class hex.anovaglm.ANOVAGLMModel

score(double[]) - Method in class hex.deeplearning.DeepLearningModel

score(double[]) - Method in class hex.glm.GLMModel

score(Frame, String, Job, boolean, CFuncRef) - Method in class hex.modelselection.ModelSelectionModel

score(Frame, String, Job, boolean, CFuncRef) - Method in class hex.rulefit.RuleFitModel

score(double[], String[][]) - Method in class hex.tree.CompressedTree

score(double[]) - Method in class hex.tree.drf.DRFModel

score(double[]) - Method in class hex.tree.gbm.GBMModel

Score - Class in hex.tree

Score the tree columns, and produce a confusion matrix and AUC

Score(SharedTree, boolean, boolean, Vec, ModelCategory, boolean, Frame, CFuncRef) - Constructor for class hex.tree.Score

Compute ModelMetrics on the testing dataset.

Score(SharedTree, Score.ScoreIncInfo, boolean, Vec, ModelCategory, boolean, Frame, CFuncRef) - Constructor for class hex.tree.Score

Score.ScoreExtension - Class in hex.tree

Score.ScoreIncInfo - Class in hex.tree

score0(double[], double[]) - Method in class hex.adaboost.AdaBoostModel

score0(double[], double[]) - Method in class hex.aggregator.AggregatorModel

score0(double[], double[]) - Method in class hex.anovaglm.ANOVAGLMModel

score0(double[], double[]) - Method in class hex.coxph.CoxPHModel

score0(double[], double[]) - Method in class hex.deeplearning.DeepLearningModel

score0(double[], double[], double) - Method in class hex.deeplearning.DeepLearningModel

Predict from raw double values representing the data

score0(double[], double[]) - Method in class hex.ensemble.StackedEnsembleModel

Should never be called: the code paths that normally go here should call predictScoreImpl().

score0(double[], double[]) - Method in class hex.gam.GAMModel

score0(double[], double[]) - Method in class hex.generic.GenericModel

score0(double[], double[], double) - Method in class hex.generic.GenericModel

score0(double[], double[]) - Method in class hex.glm.GLMModel

score0(double[], double[], double) - Method in class hex.glm.GLMModel

score0(double[], double[]) - Method in class hex.glrm.GLRMModel

score0(double[], double[]) - Method in class hex.grep.GrepModel

score0(double[], double[]) - Method in class hex.hglm.HGLMModel

score0(double[], double[]) - Method in class hex.isotonic.IsotonicRegressionModel

score0(double[], double[], double) - Method in class hex.kmeans.KMeansModel

score0(double[], double[]) - Method in class hex.kmeans.KMeansModel

score0(double[], double[]) - Method in class hex.modelselection.ModelSelectionModel

score0(double[], double[]) - Method in class hex.naivebayes.NaiveBayesModel

score0(double[], double[]) - Method in class hex.pca.PCAModel

score0(double[], double[]) - Method in class hex.psvm.PSVMModel

score0(double[], double[]) - Method in class hex.rulefit.RuleFitModel

score0(double[], double[]) - Method in class hex.svd.SVDModel

score0(double[], double[], double, int) - Method in class hex.tree.drf.DRFModel

Bulk scoring API for one row.

score0(double[], double[]) - Method in class hex.tree.dt.DTModel

score0(double[], double[], int) - Method in class hex.tree.DTreeScorer

score0(double[], double[], double, int) - Method in class hex.tree.gbm.GBMModel

Bulk scoring API for one row.

score0(double[], double[], double, int) - Method in class hex.tree.isofor.IsolationForestModel

Bulk scoring API for one row.

score0(double[], double[]) - Method in class hex.tree.isoforextended.ExtendedIsolationForestModel

score0(double[], double[], double) - Method in class hex.tree.SharedTreeModel

score0(double[], double[]) - Method in class hex.tree.SharedTreeModel

score0(double[], double[], double, int) - Method in class hex.tree.SharedTreeModel

score0(double[], double[], double, int, int) - Method in class hex.tree.SharedTreeModel

score0(double[], double[], double, int) - Method in class hex.tree.uplift.UpliftDRFModel

Bulk scoring API for one row.

score0(Chunk[], int, double[], double[]) - Method in class hex.word2vec.Word2VecModel

score0(double[], double[]) - Method in class hex.word2vec.Word2VecModel

score0Incremental(Score.ScoreIncInfo, Chunk[], double, int, double[], double[]) - Method in class hex.tree.gbm.GBMModel

score0Incremental(Score.ScoreIncInfo, Chunk[], double, int, double[], double[]) - Method in class hex.tree.SharedTreeModel

score1(Chunk[], double, double, double[], int) - Method in class hex.tree.drf.DRF

score1(Chunk[], double, double, double[], int) - Method in class hex.tree.gbm.GBM

score1(Chunk[], double, double, double[], int) - Method in class hex.tree.isofor.IsolationForest

score1(Chunk[], double, double, double[], int) - Method in class hex.tree.SharedTree

score1(Chunk[], double, double, double[], int) - Method in class hex.tree.uplift.UpliftDRF

Read the 'tree' columns, do model-specific math and put the results in the fs[] array, and return the sum.

score_decide(Chunk[], int[]) - Method in class hex.tree.ScoreBuildHistogram2

score_duty_cycle - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

Maximum fraction of wall clock time spent on model scoring on training and validation samples, and on diagnostics such as computation of feature importances (i.e., not on training).

score_indicator(Chunk[], int, double[], double[]) - Method in class hex.kmeans.KMeansModel

score_interval - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

The minimum time (in seconds) to elapse between model scoring.

score_iteration_interval - Variable in class hex.schemas.GLMV3.GLMParametersV3

score_iteration_interval - Variable in class hex.schemas.HGLMV3.HGLMParametersV3

score_iteration_interval - Variable in class hex.schemas.ModelSelectionV3.ModelSelectionParametersV3

score_ratio(Chunk[], int, double[]) - Method in class hex.kmeans.KMeansModel

score_training_samples - Variable in class hex.deeplearning.DeepLearningScoringInfo

score_training_samples() - Method in class hex.deeplearning.DeepLearningScoringInfo

score_training_samples - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

The number of training dataset points to be used for scoring.

score_training_samples - Variable in class hex.schemas.StackedEnsembleV99.StackedEnsembleParametersV99

score_tree_interval - Variable in class hex.schemas.ExtendedIsolationForestV3.ExtendedIsolationForestParametersV3

score_tree_interval - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3

score_validation_samples - Variable in class hex.deeplearning.DeepLearningScoringInfo

score_validation_samples() - Method in class hex.deeplearning.DeepLearningScoringInfo

score_validation_samples - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

The number of validation dataset points to be used for scoring.

score_validation_sampling - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

Method used to sample the validation dataset for scoring, see Score Validation Samples above.

scoreAndBuildTrees(boolean) - Method in class hex.tree.SharedTree.Driver

Build more trees, as specified by the model parameters

scoreArchetypes(Frame, Key<Frame>, boolean) - Method in class hex.glrm.GLRMModel

Project each archetype into original feature space

scoreAutoEncoder(Frame, Key, boolean) - Method in class hex.deeplearning.DeepLearningModel

Score auto-encoded reconstruction (on-the-fly, without allocating the reconstruction as done in Frame score(Frame fr))

ScoreBuildHistogram - Class in hex.tree

Score and Build Histogram

ScoreBuildHistogram(H2O.H2OCountedCompleter, int, int, int, DTree, int, DHistogram[][], DistributionFamily, int, int, int, int) - Constructor for class hex.tree.ScoreBuildHistogram

ScoreBuildHistogram2 - Class in hex.tree

Created by tomas on 10/28/16.

ScoreBuildHistogram2(SharedTree.ScoreBuildOneTree, int, int, int, int, DTree, int, DHistogram[][], DistributionFamily, int, int, int, int, int, int) - Constructor for class hex.tree.ScoreBuildHistogram2

ScoreBuildOneTree(SharedTree, int, int, DTree, int[], DHistogram[][][], Frame, boolean, float[], DistributionFamily, int, int, int, int, int, int) - Constructor for class hex.tree.SharedTree.ScoreBuildOneTree

scoreCols() - Method in class hex.tree.DTree.UndecidedNode

scoreContributions(Frame, Key<Frame>, Job<Frame>, Model.Contributions.ContributionsOptions, Frame) - Method in class hex.deeplearning.DeepLearningModel

scoreContributions(Frame, Key<Frame>, Job<Frame>, Model.Contributions.ContributionsOptions, Frame) - Method in class hex.ensemble.StackedEnsembleModel

scoreContributions(Frame, Key<Frame>) - Method in class hex.generic.GenericModel

scoreContributions(Frame, Key<Frame>, Job<Frame>) - Method in class hex.generic.GenericModel

scoreContributions(Frame, Key<Frame>, Job<Frame>, Model.Contributions.ContributionsOptions, Frame) - Method in class hex.glm.GLMModel

scoreContributions(Frame, Key<Frame>, Job<Frame>) - Method in class hex.tree.drf.DRFModel

scoreContributions(Frame, Key<Frame>, Job<Frame>, Model.Contributions.ContributionsOptions) - Method in class hex.tree.drf.DRFModel

scoreContributions(Frame, Key<Frame>) - Method in class hex.tree.SharedTreeModelWithContributions

scoreContributions(Frame, Key<Frame>, Job<Frame>) - Method in class hex.tree.SharedTreeModelWithContributions

scoreContributions(Frame, Key<Frame>, Job<Frame>, Model.Contributions.ContributionsOptions) - Method in class hex.tree.SharedTreeModelWithContributions

scoreContributions(Frame, Key<Frame>, Job<Frame>, Model.Contributions.ContributionsOptions, Frame) - Method in class hex.tree.SharedTreeModelWithContributions

ScoreContributionsSoringTaskDRF(SharedTreeModel, Model.Contributions.ContributionsOptions) - Constructor for class hex.tree.drf.DRFModel.ScoreContributionsSoringTaskDRF

ScoreContributionsSortingTask(SharedTreeModel, Model.Contributions.ContributionsOptions) - Constructor for class hex.tree.SharedTreeModelWithContributions.ScoreContributionsSortingTask

ScoreContributionsTask(SharedTreeModel) - Constructor for class hex.tree.SharedTreeModelWithContributions.ScoreContributionsTask

ScoreContributionsTaskDRF(SharedTreeModel) - Constructor for class hex.tree.drf.DRFModel.ScoreContributionsTaskDRF

ScoreContributionsWithBackgroundTask(Key<Frame>, Key<Frame>, boolean, SharedTreeModel, boolean, int[], boolean) - Constructor for class hex.tree.SharedTreeModelWithContributions.ScoreContributionsWithBackgroundTask

ScoreContributionsWithBackgroundTaskDRF(Frame, Frame, boolean, SharedTreeModel, boolean, int[]) - Constructor for class hex.tree.drf.DRFModel.ScoreContributionsWithBackgroundTaskDRF

scoreContributionsWorkEstimate(Frame, Frame, boolean) - Method in class hex.ensemble.StackedEnsembleModel

scoreDeepFeatures(Frame, int) - Method in class hex.deeplearning.DeepLearningModel

Score auto-encoded reconstruction (on-the-fly, and materialize the deep features of given layer

scoreDeepFeatures(Frame, int, Job) - Method in class hex.deeplearning.DeepLearningModel

scoreDeepFeatures(Frame, String, Job) - Method in class hex.deeplearning.DeepLearningModel

ScoreDTTask - Class in hex.tree.dt.mrtasks

ScoreDTTask(DTModel) - Constructor for class hex.tree.dt.mrtasks.ScoreDTTask

scoreExemplarMembers(Key<Frame>, int) - Method in class hex.aggregator.AggregatorModel

ScoreExtension() - Constructor for class hex.tree.Score.ScoreExtension

scoreFeatureFrequencies(Frame, Key<Frame>) - Method in class hex.tree.SharedTreeModel

ScoreIncInfo(int, int, int, int) - Constructor for class hex.tree.Score.ScoreIncInfo

scoreKeepers() - Method in class hex.glm.GLMModel

scoreKeepers() - Method in class hex.tree.SharedTreeModel.SharedTreeOutput

scoreLeafNodeAssignment(Frame, Model.LeafNodeAssignment.LeafNodeAssignmentType, Key<Frame>) - Method in class hex.tree.SharedTreeModel

scoreMetrics(Frame) - Method in class hex.gam.GAMModel

Score on an already adapted validation frame during cross validation.

scoreMetrics(Frame) - Method in class hex.glm.GLMModel

Score an already adapted frame.

scoreMetricsOnly(Frame) - Method in class hex.glrm.GLRMModel

scoreReconstruction(Frame, Key<Frame>, boolean) - Method in class hex.glrm.GLRMModel

scoreRow(DataInfo.Row, double, double[]) - Method in class hex.glm.GLMScore

scoreRow(DataInfo.Row, double[], double[], double[], int) - Method in class hex.hglm.HGLMScore

only processing gaussian for now.

scores - Variable in class hex.schemas.Word2VecSynonymsV3

scoreStagedPredictions(Frame, Key<Frame>) - Method in class hex.tree.gbm.GBMModel

scoreTree(double[], double[], int) - Method in class hex.tree.CompressedForest.LocalCompressedForest

Score given tree on the row of data.

scoreZeroTrees() - Method in class hex.tree.drf.DRF

scoreZeroTrees() - Method in class hex.tree.isofor.IsolationForest

scoreZeroTrees() - Method in class hex.tree.SharedTree

scoreZeroTrees() - Method in class hex.tree.uplift.UpliftDRF

SCORING_INTERVAL_MSEC - Static variable in class hex.glm.GLM

scoringDomains() - Method in class hex.gam.GAMModel

scoringDomains() - Method in class hex.glm.GLMModel

scoringInfo(String[], Frame) - Method in class hex.DataInfo

scoringInfo(String[], Frame, int, boolean) - Method in class hex.DataInfo

Creates a scoringInfo from a DataInfo instance created during model training

scoringInfo() - Method in class hex.DataInfo

Creates a DataInfo for scoring on a test Frame from a DataInfo instance created during model training This is a lightweight version of the method only usable for models that don't use advanced features of DataInfo (eg.

se() - Method in class hex.tree.DTree.Split

seed - Variable in class hex.schemas.AdaBoostV3.AdaBoostParametersV3

seed - Variable in class hex.schemas.AggregatorV99.AggregatorParametersV99

seed - Variable in class hex.schemas.ANOVAGLMV3.ANOVAGLMParametersV3

seed - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

The random seed controls sampling and initialization.

seed - Variable in class hex.schemas.DTV3.DTParametersV3

seed - Variable in class hex.schemas.ExtendedIsolationForestV3.ExtendedIsolationForestParametersV3

seed - Variable in class hex.schemas.GAMV3.GAMParametersV3

seed - Variable in class hex.schemas.GLMV3.GLMParametersV3

seed - Variable in class hex.schemas.GLRMV3.GLRMParametersV3

seed - Variable in class hex.schemas.HGLMV3.HGLMParametersV3

seed - Variable in class hex.schemas.KMeansV3.KMeansParametersV3

seed - Variable in class hex.schemas.ModelSelectionV3.ModelSelectionParametersV3

seed - Variable in class hex.schemas.NaiveBayesV3.NaiveBayesParametersV3

seed - Variable in class hex.schemas.PCAV3.PCAParametersV3

seed - Variable in class hex.schemas.PSVMV3.PSVMParametersV3

seed - Variable in class hex.schemas.RuleFitV3.RuleFitParametersV3

seed - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3

seed - Variable in class hex.schemas.StackedEnsembleV99.StackedEnsembleParametersV99

seed - Variable in class hex.schemas.SVDV99.SVDParametersV99

seed(int) - Static method in class hex.tree.drf.TreeMeasuresCollector.ShuffleTask

sent_sample_rate - Variable in class hex.schemas.Word2VecV3.Word2VecParametersV3

seP1NA() - Method in class hex.tree.DHistogram

Squared Error for NA bucket and prediction value _pred1

seP2NA() - Method in class hex.tree.DHistogram

Squared Error for NA bucket and prediction value _pred2

separate_linear_beta - Variable in class hex.schemas.GLMV3.GLMParametersV3

set(int, int, double) - Method in class hex.coxph.Storage.DenseRowMatrix

set(int, int, double) - Method in interface hex.coxph.Storage.Matrix

set(int, int, float) - Method in class hex.deeplearning.Storage.DenseColMatrix

set(int, int, float) - Method in class hex.deeplearning.Storage.DenseRowMatrix

set(int, double) - Method in class hex.deeplearning.Storage.DenseVector

set(int, int, float) - Method in interface hex.deeplearning.Storage.Matrix

set(int, int, float) - Method in class hex.deeplearning.Storage.SparseRowMatrix

set(int, int, int, float) - Method in interface hex.deeplearning.Storage.Tensor

set(int, double) - Method in interface hex.deeplearning.Storage.Vector

set_params(DeepLearningModel.DeepLearningParameters, Key<Model>) - Method in class hex.deeplearning.DeepLearningModelInfo

set_processed_global(long) - Method in class hex.deeplearning.DeepLearningModelInfo

set_processed_local(long) - Method in class hex.deeplearning.DeepLearningModelInfo

setActiveClass(int) - Method in class hex.glm.ComputationState

setActiveDataMultinomialNull() - Method in class hex.glm.ComputationState

setActiveDataNull() - Method in class hex.glm.ComputationState

setAllIn(boolean) - Method in class hex.glm.ComputationState

setAlpha(double) - Method in class hex.glm.ComputationState

setAlphai(boolean, boolean) - Method in class hex.optimization.OptimizationUtils.ExactLineSearch

setBC(GLM.BetaConstraint) - Method in class hex.glm.ComputationState

setBeta(double[]) - Method in class hex.glm.ComputationState

setBeta(double[]) - Method in class hex.hglm.ComputationStateHGLM

setBetaConstraintsDeriv(double[], double[], ComputationState, ConstrainedGLMUtils.LinearConstraints[], ConstrainedGLMUtils.LinearConstraints[], GLM.GLMGradientSolver, double[]) - Method in class hex.optimization.OptimizationUtils.ExactLineSearch

setBetaDiff(double) - Method in class hex.glm.ComputationState

setBetaMultinomial(int, double[], double[]) - Method in class hex.glm.ComputationState

setBitSet(BitSet, int[]) - Static method in class hex.modelselection.ModelSelectionUtils

setCalibrationFrame(Frame) - Method in interface hex.tree.CalibrationHelper.ModelBuilderWithCalibration

setCalibrationFrame(Frame) - Method in class hex.tree.SharedTree

setCalibrationMethod(CalibrationHelper.CalibrationMethod) - Method in interface hex.tree.CalibrationHelper.ParamsWithCalibration

setCalibrationMethod(CalibrationHelper.CalibrationMethod) - Method in class hex.tree.SharedTreeModel.SharedTreeParameters

setCalibrationModel(Model<?, ?, ?>) - Method in interface hex.tree.CalibrationHelper.OutputWithCalibration

setCalibrationModel(Model<?, ?, ?>) - Method in class hex.tree.SharedTreeModel.SharedTreeOutput

setCatNAFill(int[]) - Method in class hex.DataInfo

setCoefficient(double) - Method in class hex.rulefit.Rule

setCombo(int[], int, int) - Static method in class hex.gam.GamSplines.ThinPlateRegressionUtils

setCommonParams(P) - Method in class hex.ensemble.Metalearner

setConstIndices(Map<DispersionTask.ConstColNames, Integer>, int) - Static method in class hex.glm.DispersionTask.ComputeMaxSumSeriesTsk

setConstraintInfo(GLM.GLMGradientInfo, ConstrainedGLMUtils.LinearConstraints[], ConstrainedGLMUtils.LinearConstraints[], double[], double[]) - Method in class hex.glm.ComputationState

setCriterionValue(double) - Method in class hex.tree.dt.AbstractSplittingRule

setCriterionValue(double) - Method in class hex.tree.dt.binning.SplitStatistics

setCrossValidationParams(P) - Method in class hex.ensemble.Metalearner

setCustomParams(P) - Method in class hex.ensemble.Metalearner

setDebugParams(SharedTree.SharedTreeDebugParams) - Method in class hex.tree.SharedTree

Modify algorithm inner workings - only meant for development

setDebugValues(int, int, double, double, double, double, int, int, int, int, int, int, double, double, double, double, double, double, Chunk[], Map<DispersionTask.InfoColNames, Integer>, double) - Method in class hex.glm.DispersionTask.ComputeMaxSumSeriesTsk

setDefaultAuucThresholds(double[]) - Method in class hex.tree.uplift.UpliftDRFModel.UpliftDRFOutput

setDefaultBSType(GAMModel.GAMParameters) - Static method in class hex.gam.MatrixFrameUtils.GamUtils

setDefaultScale(GAMModel.GAMParameters) - Static method in class hex.gam.MatrixFrameUtils.GamUtils

setDiagValues(double[][], double) - Static method in class hex.hglm.HGLMUtils

setDispersion(double, boolean) - Method in class hex.glm.GLMModel

setDistributionFamily(DistributionFamily) - Method in class hex.anovaglm.ANOVAGLMModel.ANOVAGLMParameters

setDistributionFamily(DistributionFamily) - Method in class hex.ensemble.StackedEnsembleModel.StackedEnsembleParameters

setDistributionFamily(DistributionFamily) - Method in class hex.gam.GAMModel.GAMParameters

setDistributionFamily(DistributionFamily) - Method in class hex.glm.GLMModel.GLMParameters

setFeatureIndex(int) - Method in class hex.tree.dt.AbstractSplittingRule

setFeatureIndex(int) - Method in class hex.tree.dt.binning.SplitStatistics

setGamParameters(GAMModel.GAMParameters, int, int) - Static method in class hex.gam.MatrixFrameUtils.GamUtils

setGamPredSize(GAMModel.GAMParameters, int) - Static method in class hex.gam.MatrixFrameUtils.GamUtils

For each spline type, calculate the gam columns in each gam column group.

setGinfo(GLM.GLMGradientInfo) - Method in class hex.glm.ComputationState

setgMax(double) - Method in class hex.glm.ComputationState

setGradEps(double) - Method in class hex.optimization.L_BFGS

setGradientErr(double) - Method in class hex.glm.ComputationState

setGradientNorm(MathUtils.Norm) - Method in class hex.optimization.ADMM.L1Solver

setGslvrNull() - Method in class hex.glm.ComputationState

setHistorySz(int) - Method in class hex.optimization.L_BFGS

setInfoIndices(Map<DispersionTask.InfoColNames, Integer>, int, boolean) - Static method in class hex.glm.DispersionTask.ComputeMaxSumSeriesTsk

setInitialStep(double) - Method in interface hex.optimization.OptimizationUtils.LineSearchSolver

setInitialStep(double) - Method in class hex.optimization.OptimizationUtils.MoreThuente

setInitialStep(double) - Method in class hex.optimization.OptimizationUtils.SimpleBacktrackingLS

setInput(long, double[], int) - Method in class hex.deeplearning.Neurons.Input

One of two methods to set layer input values.

setInput(long, int[], double[], int, int[], int) - Method in class hex.deeplearning.Neurons.Input

The second method used to set input layer values.

setIter(int) - Method in class hex.glm.ComputationState

setLambda(double) - Method in class hex.glm.ComputationState

setLambdaMax(double) - Method in class hex.glm.ComputationState

setLambdas(GLMModel.GLMParameters) - Method in class hex.glm.GLMModel.GLMOutput

setLambdaSimple(double) - Method in class hex.glm.ComputationState

setLikelihood(double) - Method in class hex.glm.ComputationState

setLinearConstraints(ConstrainedGLMUtils.LinearConstraints[], ConstrainedGLMUtils.LinearConstraints[], boolean) - Method in class hex.glm.ComputationState

setMax(double) - Method in class hex.tree.dt.binning.NumericBin

setMaxIter(int) - Method in class hex.optimization.L_BFGS

setMin(double) - Method in class hex.tree.dt.binning.NumericBin

setModelOutput(HGLMTask.ComputationEngineTask) - Method in class hex.hglm.HGLMModel.HGLMModelOutput

setModelOutputFields(ComputationStateHGLM) - Method in class hex.hglm.HGLMModel.HGLMModelOutput

setModelOutputFixMatVec(HGLMTask.ComputationEngineTask) - Method in class hex.hglm.HGLMModel.HGLMModelOutput

For debugging only.

setNewMask(boolean[]) - Method in class hex.tree.dt.CategoricalFeatureLimits

setNewMaskExcluded(boolean[]) - Method in class hex.tree.dt.CategoricalFeatureLimits

setNewMax(double) - Method in class hex.tree.dt.NumericFeatureLimits

setNewMin(double) - Method in class hex.tree.dt.NumericFeatureLimits

setNonNegative() - Method in class hex.glm.GLM.BetaConstraint

setNonNegative(Frame) - Method in class hex.glm.GLM.BetaConstraint

setNumTrees(int) - Method in class hex.tree.TreeStats

setObjEps(double) - Method in class hex.optimization.L_BFGS

setOutputLayerGradient(double, int, int) - Method in class hex.deeplearning.Neurons.Linear

Backpropagation for regression

setOutputLayerGradient(double, int, int) - Method in class hex.deeplearning.Neurons

Accumulation of reconstruction errors for a generic Neurons class (This is only used for AutoEncoders)

setOutputLayerGradient(double, int, int) - Method in class hex.deeplearning.Neurons.Softmax

Part of backpropagation for classification Update every weight as follows: w += -rate * dE/dw Compute dE/dw via chain rule: dE/dw = dE/dy * dy/dnet * dnet/dw, where net = sum(xi*wi)+b and y = activation function

setParamField(Model.Parameters, Model.Parameters, boolean, Field[], List<String>) - Static method in class hex.gam.MatrixFrameUtils.GamUtils

setParamField(Model.Parameters, GLMModel.GLMParameters, boolean, Field[], List<String>) - Static method in class hex.modelselection.ModelSelectionUtils

setPredictorTransform(DataInfo.TransformType) - Method in class hex.DataInfo

setResponse(int, double) - Method in class hex.DataInfo.Row

setResponse(String, Vec) - Method in class hex.DataInfo

setResponse(String, Vec, int) - Method in class hex.DataInfo

setResponseTransform(DataInfo.TransformType) - Method in class hex.DataInfo

setSparse(boolean) - Method in class hex.FrameTask2

setSPD(boolean) - Method in class hex.gram.Gram.Cholesky

setStartIndex(int) - Method in class hex.ContributionsMeanAggregator

setSubmodelIdx(int, GLMModel.GLMParameters) - Method in class hex.glm.GLMModel.GLMOutput

setT(double[][]) - Method in class hex.hglm.ComputationStateHGLM

setTauEVarE10(double) - Method in class hex.hglm.ComputationStateHGLM

setThinPlateParameters(GAMModel.GAMParameters, int) - Static method in class hex.gam.MatrixFrameUtils.GamUtils

setUbeta(double[][]) - Method in class hex.hglm.ComputationStateHGLM

setUnstable() - Method in class hex.deeplearning.DeepLearningModelInfo

setupBigScorePredict(Model<GenericModel, GenericModelParameters, GenericModelOutput>.BigScore) - Method in class hex.generic.GenericModel

setupBigScorePredict(Model<PSVMModel, PSVMModel.PSVMParameters, PSVMModel.PSVMModelOutput>.BigScore) - Method in class hex.psvm.PSVMModel

setupLocal() - Method in class hex.deeplearning.DeepLearningTask

Transfer ownership from global (shared) model to local model which will be worked on

setupLocal() - Method in class hex.deeplearning.DeepLearningTask2

Do the local computation: Perform one DeepLearningTask (with run_local=true) iteration.

setupLocal() - Method in class hex.FrameTask

setupLocal() - Method in class hex.FrameTask2

setupLocal() - Method in class hex.glm.GLMTask.YMUTask

setupLocal() - Method in class hex.glrm.GLRMGenX

setupLocal() - Method in class hex.tree.drf.TreeMeasuresCollector

setupLocal() - Method in class hex.tree.DTreeScorer

setupLocal() - Method in class hex.tree.ScoreBuildHistogram2

setupLocal() - Method in class hex.tree.SharedTreeModelWithContributions.ScoreContributionsTask

setupLocal() - Method in class hex.tree.SharedTreeModelWithContributions.ScoreContributionsWithBackgroundTask

setupLocal() - Method in class hex.word2vec.WordVectorConverter

setupLocal() - Method in class hex.word2vec.WordVectorTrainer

setVarName(String) - Method in class hex.rulefit.Rule

setVcov(double[][]) - Method in class hex.glm.GLMModel

setWeights(String, Vec) - Method in class hex.DataInfo

setWideDataset(boolean) - Method in class hex.glrm.GLRM

setWideDataset(boolean) - Method in class hex.pca.PCA

setWideDataset(boolean) - Method in class hex.svd.SVD

setZValues(double[], boolean) - Method in class hex.glm.ComputationState

setZValues(double[], double, boolean) - Method in class hex.glm.GLMModel

SharedTree<M extends SharedTreeModel<M,P,O>,P extends SharedTreeModel.SharedTreeParameters,O extends SharedTreeModel.SharedTreeOutput> - Class in hex.tree

SharedTree(P) - Constructor for class hex.tree.SharedTree

SharedTree(P, Key<M>) - Constructor for class hex.tree.SharedTree

SharedTree(P, Job) - Constructor for class hex.tree.SharedTree

SharedTree(P, boolean) - Constructor for class hex.tree.SharedTree

SharedTree.Driver - Class in hex.tree

SharedTree.FrameMap - Class in hex.tree

SharedTree.ScoreBuildOneTree - Class in hex.tree

SharedTree.SharedTreeDebugParams - Class in hex.tree

SharedTreeDebugParams(boolean) - Constructor for class hex.tree.SharedTree.SharedTreeDebugParams

SharedTreeDebugParams() - Constructor for class hex.tree.SharedTree.SharedTreeDebugParams

SharedTreeModel<M extends SharedTreeModel<M,P,O>,P extends SharedTreeModel.SharedTreeParameters,O extends SharedTreeModel.SharedTreeOutput> - Class in hex.tree

SharedTreeModel(Key<M>, P, O) - Constructor for class hex.tree.SharedTreeModel

SharedTreeModel.BufStringDecisionPathTracker - Class in hex.tree

SharedTreeModel.SharedTreeOutput - Class in hex.tree

SharedTreeModel.SharedTreeParameters - Class in hex.tree

SharedTreeModel.SharedTreeParameters.HistogramType - Enum in hex.tree

SharedTreeModelOutputV3() - Constructor for class hex.schemas.SharedTreeModelV3.SharedTreeModelOutputV3

SharedTreeModelV3<M extends SharedTreeModel<M,P,O>,S extends SharedTreeModelV3<M,S,P,PS,O,OS>,P extends SharedTreeModel.SharedTreeParameters,PS extends SharedTreeV3.SharedTreeParametersV3<P,PS>,O extends SharedTreeModel.SharedTreeOutput,OS extends SharedTreeModelV3.SharedTreeModelOutputV3<O,OS>> - Class in hex.schemas

SharedTreeModelV3() - Constructor for class hex.schemas.SharedTreeModelV3

SharedTreeModelV3.SharedTreeModelOutputV3<O extends SharedTreeModel.SharedTreeOutput,SO extends SharedTreeModelV3.SharedTreeModelOutputV3<O,SO>> - Class in hex.schemas

SharedTreeModelWithContributions<M extends SharedTreeModel<M,P,O>,P extends SharedTreeModel.SharedTreeParameters,O extends SharedTreeModel.SharedTreeOutput> - Class in hex.tree

SharedTreeModelWithContributions(Key<M>, P, O) - Constructor for class hex.tree.SharedTreeModelWithContributions

SharedTreeModelWithContributions.ScoreContributionsSortingTask - Class in hex.tree

SharedTreeModelWithContributions.ScoreContributionsTask - Class in hex.tree

SharedTreeModelWithContributions.ScoreContributionsWithBackgroundTask - Class in hex.tree

SharedTreeMojoWriter<M extends SharedTreeModel<M,P,O>,P extends SharedTreeModel.SharedTreeParameters,O extends SharedTreeModel.SharedTreeOutput> - Class in hex.tree

Shared Mojo definition file for DRF and GBM models.

SharedTreeMojoWriter() - Constructor for class hex.tree.SharedTreeMojoWriter

SharedTreeMojoWriter(M) - Constructor for class hex.tree.SharedTreeMojoWriter

SharedTreeOutput(SharedTree) - Constructor for class hex.tree.SharedTreeModel.SharedTreeOutput

SharedTreeParameters() - Constructor for class hex.tree.SharedTreeModel.SharedTreeParameters

SharedTreeParametersV3() - Constructor for class hex.schemas.SharedTreeV3.SharedTreeParametersV3

SharedTreePojoWriter - Class in hex.tree

SharedTreePojoWriter(Key<?>, Model.Output, CategoricalEncoding, boolean, CompressedTree[][], TreeStats) - Constructor for class hex.tree.SharedTreePojoWriter

SharedTreeV3<B extends SharedTree,S extends SharedTreeV3<B,S,P>,P extends SharedTreeV3.SharedTreeParametersV3> - Class in hex.schemas

SharedTreeV3() - Constructor for class hex.schemas.SharedTreeV3

SharedTreeV3.SharedTreeParametersV3<P extends SharedTreeModel.SharedTreeParameters,S extends SharedTreeV3.SharedTreeParametersV3<P,S>> - Class in hex.schemas

shouldReorder(Vec) - Method in class hex.tree.SharedTree

shrinkage(double, double) - Static method in class hex.optimization.ADMM

shrinkArrays(int) - Method in class hex.modelselection.ModelSelectionModel.ModelSelectionModelOutput

shrinkDoubleArray(double[][], int) - Static method in class hex.modelselection.ModelSelectionUtils

shrinkFullArray(double[]) - Method in class hex.glm.ComputationState

shrinkKeyArray(Key[], int) - Static method in class hex.modelselection.ModelSelectionUtils

shrinkStringArray(String[][], int) - Static method in class hex.modelselection.ModelSelectionUtils

shuffle(Vec) - Static method in class hex.tree.drf.TreeMeasuresCollector.ShuffleTask

shuffle_training_data - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

Enable shuffling of training data (on each node).

ShuffleSplitFrame - Class in hex.splitframe

Frame splitter function to divide given frame into multiple partitions based on given ratios.

ShuffleSplitFrame() - Constructor for class hex.splitframe.ShuffleSplitFrame

shuffleSplitFrame(Frame, Key<Frame>[], double[], long) - Static method in class hex.splitframe.ShuffleSplitFrame

ShuffleTask() - Constructor for class hex.tree.drf.TreeMeasuresCollector.ShuffleTask

SimpleBacktrackingLS(OptimizationUtils.GradientSolver, double[], double) - Constructor for class hex.optimization.OptimizationUtils.SimpleBacktrackingLS

SimpleBacktrackingLS(OptimizationUtils.GradientSolver, double[], double, OptimizationUtils.GradientInfo) - Constructor for class hex.optimization.OptimizationUtils.SimpleBacktrackingLS

SimpleMetalearner(String) - Constructor for class hex.ensemble.Metalearners.SimpleMetalearner

single_node_mode - Variable in class hex.schemas.CoxPHV3.CoxPHParametersV3

single_node_mode - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

Run on a single node for fine-tuning of model parameters.

singular_vals - Variable in class hex.schemas.GLRMModelV3.GLRMModelOutputV3

size() - Method in class hex.coxph.Storage.DenseRowMatrix

size() - Method in interface hex.coxph.Storage.Matrix

size() - Method in class hex.deeplearning.DeepLearningModelInfo

size() - Method in class hex.deeplearning.Storage.DenseColMatrix

size() - Method in class hex.deeplearning.Storage.DenseRowMatrix

size() - Method in class hex.deeplearning.Storage.DenseVector

size() - Method in interface hex.deeplearning.Storage.Matrix

size() - Method in class hex.deeplearning.Storage.SparseRowMatrix

size() - Method in interface hex.deeplearning.Storage.Tensor

size() - Method in interface hex.deeplearning.Storage.Vector

size() - Method in class hex.rulefit.RuleEnsemble

size() - Method in class hex.tree.DTree.DecidedNode

size() - Method in class hex.tree.DTree.LeafNode

size() - Method in class hex.tree.DTree.Node

size() - Method in class hex.tree.DTree.UndecidedNode

skip_missing - Variable in class hex.schemas.GramV3

skipRow(long) - Method in class hex.FrameTask

slices() - Method in interface hex.deeplearning.Storage.Tensor

SMulTask(DataInfo, int) - Constructor for class hex.util.LinearAlgebraUtils.SMulTask

SMulTask(DataInfo, int, int) - Constructor for class hex.util.LinearAlgebraUtils.SMulTask

Softmax(int) - Constructor for class hex.deeplearning.Neurons.Softmax

solve(double[]) - Method in class hex.glm.GLM.GramSolver

solve(double[], double[]) - Method in class hex.glm.GLM.GramSolver

solve(double[], double[]) - Method in class hex.glm.GLM.ProximalGradientSolver

solve(double[][]) - Method in class hex.gram.Gram.Cholesky

solve(double[]) - Method in class hex.gram.Gram.Cholesky

Find solution to A*x = y.

solve(ADMM.ProximalSolver, double[], double, boolean) - Method in class hex.optimization.ADMM.L1Solver

solve(ADMM.ProximalSolver, double[], double, boolean, double[], double[]) - Method in class hex.optimization.ADMM.L1Solver

solve(double[], double[]) - Method in interface hex.optimization.ADMM.ProximalSolver

solve(OptimizationUtils.GradientSolver, double[], OptimizationUtils.GradientInfo, L_BFGS.ProgressMonitor) - Method in class hex.optimization.L_BFGS

Solve the optimization problem defined by the user-supplied ginfo function using L-BFGS algorithm.

solve(OptimizationUtils.GradientSolver, double[]) - Method in class hex.optimization.L_BFGS

Solve the optimization problem defined by the user-supplied ginfo function using L-BFGS algorithm.

solve(Frame, Vec, PrimalDualIPM.Parms, PrimalDualIPM.ProgressObserver) - Static method in class hex.psvm.psvm.PrimalDualIPM

solver - Variable in class hex.schemas.ANOVAGLMV3.ANOVAGLMParametersV3

solver - Variable in class hex.schemas.GAMV3.GAMParametersV3

solver - Variable in class hex.schemas.GLMV3.GLMParametersV3

solver - Variable in class hex.schemas.ModelSelectionV3.ModelSelectionParametersV3

sortCoeffMags(int, double[]) - Static method in class hex.gam.MatrixFrameUtils.GamUtils

sortGAMParameters(GAMModel.GAMParameters, int, int, int) - Static method in class hex.gam.MatrixFrameUtils.GamUtils

move CS spline smoothers to the front and TP spline smoothers to the back for arrays: gam_columns, bs, scale, num_knots.

sparse - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

sparseness() - Method in class hex.gram.Gram

sparseOffset(double[], DataInfo) - Static method in class hex.glm.GLM

sparsity_beta - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

spline_orders - Variable in class hex.schemas.GAMV3.GAMParametersV3

SPLINENOTIMPL - Static variable in class hex.gam.MatrixFrameUtils.GamUtils

splines_non_negative - Variable in class hex.schemas.GAMV3.GAMParametersV3

Split(int, int, DHistogram.NASplitDir, IcedBitSet, byte, double, double, double, double, double, double, double, double, double) - Constructor for class hex.tree.DTree.Split

Split(int, int, DHistogram.NASplitDir, IcedBitSet, byte, double, double, double, double, double, double, double, double, double, double, double, double, double, double, double, double, double, double, double) - Constructor for class hex.tree.DTree.Split

split(double, double, double, double, double, double) - Method in class hex.tree.uplift.Divergence

Calculate gain after split

SplitStatistics - Class in hex.tree.dt.binning

Potential split including splitting rule and statistics on count of samples and distribution of target variable.

SplitStatistics() - Constructor for class hex.tree.dt.binning.SplitStatistics

sqrtDiag(double[][]) - Static method in class hex.util.LinearAlgebraUtils

Given a matrix aMat as a double [][] array, this function will return an array that is the square root of the diagonals of aMat.

StackedEnsemble - Class in hex.ensemble

An ensemble of other models, created by stacking with the SuperLearner algorithm or a variation.

StackedEnsemble(StackedEnsembleModel.StackedEnsembleParameters) - Constructor for class hex.ensemble.StackedEnsemble

StackedEnsemble(boolean) - Constructor for class hex.ensemble.StackedEnsemble

StackedEnsembleModel - Class in hex.ensemble

An ensemble of other models, created by stacking with the SuperLearner algorithm or a variation.

StackedEnsembleModel(Key, StackedEnsembleModel.StackedEnsembleParameters, StackedEnsembleModel.StackedEnsembleOutput) - Constructor for class hex.ensemble.StackedEnsembleModel

StackedEnsembleModel.StackedEnsembleOutput - Class in hex.ensemble

StackedEnsembleModel.StackedEnsembleParameters - Class in hex.ensemble

StackedEnsembleModel.StackedEnsembleParameters.MetalearnerTransform - Enum in hex.ensemble

StackedEnsembleModel.StackingStrategy - Enum in hex.ensemble

StackedEnsembleModelOutputV99() - Constructor for class hex.schemas.StackedEnsembleModelV99.StackedEnsembleModelOutputV99

StackedEnsembleModelV99 - Class in hex.schemas

StackedEnsembleModelV99() - Constructor for class hex.schemas.StackedEnsembleModelV99

StackedEnsembleModelV99.StackedEnsembleModelOutputV99 - Class in hex.schemas

StackedEnsembleModelV99.StackingStrategyProvider - Class in hex.schemas

StackedEnsembleMojoWriter - Class in hex.ensemble

StackedEnsembleMojoWriter() - Constructor for class hex.ensemble.StackedEnsembleMojoWriter

StackedEnsembleMojoWriter(StackedEnsembleModel) - Constructor for class hex.ensemble.StackedEnsembleMojoWriter

StackedEnsembleOutput() - Constructor for class hex.ensemble.StackedEnsembleModel.StackedEnsembleOutput

StackedEnsembleOutput(StackedEnsemble) - Constructor for class hex.ensemble.StackedEnsembleModel.StackedEnsembleOutput

StackedEnsembleOutput(Job) - Constructor for class hex.ensemble.StackedEnsembleModel.StackedEnsembleOutput

StackedEnsembleParameters() - Constructor for class hex.ensemble.StackedEnsembleModel.StackedEnsembleParameters

StackedEnsembleParametersV99() - Constructor for class hex.schemas.StackedEnsembleV99.StackedEnsembleParametersV99

StackedEnsembleV99 - Class in hex.schemas

StackedEnsembleV99() - Constructor for class hex.schemas.StackedEnsembleV99

StackedEnsembleV99.StackedEnsembleParametersV99 - Class in hex.schemas

StackedEnsembleV99.StackedEnsembleParametersV99.AlgorithmValuesProvider - Class in hex.schemas

StackingStrategyProvider() - Constructor for class hex.schemas.StackedEnsembleModelV99.StackingStrategyProvider

standardize(double[], double[]) - Method in class hex.DataInfo.Row

standardize - Variable in class hex.schemas.ANOVAGLMV3.ANOVAGLMParametersV3

standardize - Variable in class hex.schemas.DataInfoFrameV3

standardize - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

standardize - Variable in class hex.schemas.GAMV3.GAMParametersV3

standardize - Variable in class hex.schemas.GLMV3.GLMParametersV3

standardize - Variable in class hex.schemas.GramV3

standardize - Variable in class hex.schemas.KMeansV3.KMeansParametersV3

standardize - Variable in class hex.schemas.ModelSelectionV3.ModelSelectionParametersV3

standardize_tp_gam_cols - Variable in class hex.schemas.GAMV3.GAMParametersV3

start_column - Variable in class hex.schemas.CoxPHV3.CoxPHParametersV3

startCoefs(int, long) - Static method in class hex.optimization.L_BFGS

startval - Variable in class hex.schemas.GAMV3.GAMParametersV3

startval - Variable in class hex.schemas.GLMV3.GLMParametersV3

startval - Variable in class hex.schemas.ModelSelectionV3.ModelSelectionParametersV3

std_errs - Variable in class hex.schemas.GLMRegularizationPathV3

stdErr() - Method in class hex.glm.GLMModel.GLMOutput

stdErr() - Method in class hex.glm.GLMModel.Submodel

stdErr(double[], double[]) - Method in class hex.glm.GLMModel.Submodel

step() - Method in interface hex.optimization.OptimizationUtils.LineSearchSolver

step() - Method in class hex.optimization.OptimizationUtils.MoreThuente

step() - Method in class hex.optimization.OptimizationUtils.SimpleBacktrackingLS

step_size - Variable in class hex.schemas.GLRMModelV3.GLRMModelOutputV3

stop_column - Variable in class hex.schemas.CoxPHV3.CoxPHParametersV3

stopped_early - Variable in class hex.deeplearning.DeepLearningModel

Storage - Class in hex.coxph

Storage() - Constructor for class hex.coxph.Storage

Storage - Class in hex.deeplearning

Storage() - Constructor for class hex.deeplearning.Storage

Storage.DenseColMatrix - Class in hex.deeplearning

Dense column matrix implementation

Storage.DenseRowMatrix - Class in hex.coxph

Dense row matrix implementation

Storage.DenseRowMatrix - Class in hex.deeplearning

Dense row matrix implementation

Storage.DenseVector - Class in hex.deeplearning

Dense vector implementation

Storage.Matrix - Interface in hex.coxph

Abstract matrix interface

Storage.Matrix - Interface in hex.deeplearning

Abstract matrix interface

Storage.SparseRowMatrix - Class in hex.deeplearning

Sparse row matrix implementation

Storage.Tensor - Interface in hex.deeplearning

Abstract tensor interface

Storage.Vector - Interface in hex.deeplearning

Abstract vector interface

store_knot_locations - Variable in class hex.schemas.GAMV3.GAMParametersV3

str() - Method in class water.rapids.prims.AstPredictedVsActualByVar

str() - Method in class water.rapids.prims.AstSetCalibrationModel

str() - Method in class water.rapids.prims.isotonic.AstPoolAdjacentViolators

str() - Method in class water.rapids.prims.rulefit.AstPredictRule

str() - Method in class water.rapids.prims.tree.AstTreeUpdateWeights

str() - Method in class water.rapids.prims.word2vec.AstWord2VecToFrame

stratify_by - Variable in class hex.schemas.CoxPHV3.CoxPHParametersV3

subgrad(double, double[], double[]) - Static method in class hex.optimization.ADMM

Submodel(double, double, double[], int, double, double, int, double[], boolean) - Constructor for class hex.glm.GLMModel.Submodel

sumAfjAfjAfjTYj(double[][][], double[][], double[][], double[]) - Static method in class hex.hglm.HGLMTask.ComputationEngineTask

sumGramConstribution(ConstrainedGLMUtils.ConstraintsGram[], int) - Static method in class hex.glm.ConstrainedGLMUtils

summaryTable - Variable in class hex.deeplearning.DeepLearningModelInfo

sumOfRowWeights - Variable in class hex.glm.ComputationState.GramXY

surrogate_gap_threshold - Variable in class hex.schemas.PSVMV3.PSVMParametersV3

sv_threshold - Variable in class hex.schemas.PSVMV3.PSVMParametersV3

SVD - Class in hex.svd

Singular Value Decomposition SVD via Power Method Algorithm Proof of Convergence for Power Method Randomized Algorithms for Matrix Approximation

SVD(SVDModel.SVDParameters) - Constructor for class hex.svd.SVD

SVD(SVDModel.SVDParameters, Job) - Constructor for class hex.svd.SVD

SVD(SVDModel.SVDParameters, Job, boolean, GLRMModel) - Constructor for class hex.svd.SVD

SVD(boolean) - Constructor for class hex.svd.SVD

svd_method - Variable in class hex.schemas.GLRMV3.GLRMParametersV3

svd_method - Variable in class hex.schemas.SVDV99.SVDParametersV99

SVDModel - Class in hex.svd

SVDModel(Key<SVDModel>, SVDModel.SVDParameters, SVDModel.SVDOutput) - Constructor for class hex.svd.SVDModel

SVDModel.ModelMetricsSVD - Class in hex.svd

SVDModel.ModelMetricsSVD.SVDModelMetrics - Class in hex.svd

SVDModel.SVDOutput - Class in hex.svd

SVDModel.SVDParameters - Class in hex.svd

SVDModel.SVDParameters.Method - Enum in hex.svd

SVDModelMetrics(int) - Constructor for class hex.svd.SVDModel.ModelMetricsSVD.SVDModelMetrics

SVDModelOutputV99() - Constructor for class hex.schemas.SVDModelV99.SVDModelOutputV99

SVDModelV99 - Class in hex.schemas

SVDModelV99() - Constructor for class hex.schemas.SVDModelV99

SVDModelV99.SVDModelOutputV99 - Class in hex.schemas

SVDOutput(SVD) - Constructor for class hex.svd.SVDModel.SVDOutput

SVDParameters() - Constructor for class hex.svd.SVDModel.SVDParameters

SVDParametersV99() - Constructor for class hex.schemas.SVDV99.SVDParametersV99

SVDV99 - Class in hex.schemas

SVDV99() - Constructor for class hex.schemas.SVDV99

SVDV99.SVDParametersV99 - Class in hex.schemas

svs_count - Variable in class hex.schemas.PSVMModelV3.PSVMModelOutputV3

sweepCPM(double[][], int[], boolean) - Static method in class hex.modelselection.ModelSelectionUtils

This method perform the sweeping action described in section II of doc.

sweepCPMElements(Set<ModelSelectionUtils.SweepElement>[], double[][]) - Static method in class hex.modelselection.ModelSelectionUtils

sweepCPMParallel(Frame, int[], int[]) - Static method in class hex.modelselection.ModelSelectionUtils

SweepFrameParallel(int[], int, Frame) - Constructor for class hex.modelselection.ModelSelectionTasks.SweepFrameParallel

SweepModel(int[], double[][], double) - Constructor for class hex.modelselection.ModelSelection.SweepModel

sweepMSE(double[][], List<Integer>) - Static method in class hex.modelselection.ModelSelectionUtils

This function performs sweeping on the last row and column only to update the variance error to reduce computation time.

SweepVector(int, int, double) - Constructor for class hex.modelselection.ModelSelectionUtils.SweepVector

synonyms - Variable in class hex.schemas.Word2VecSynonymsV3

T

Tanh(int) - Constructor for class hex.deeplearning.Neurons.Tanh

TanhDropout(int) - Constructor for class hex.deeplearning.Neurons.TanhDropout

target_num_exemplars - Variable in class hex.schemas.AggregatorV99.AggregatorParametersV99

target_ratio_comm_to_comp - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

tau_e_var_init - Variable in class hex.schemas.HGLMV3.HGLMParametersV3

tau_u_var_init - Variable in class hex.schemas.HGLMV3.HGLMParametersV3

terminate() - Method in class hex.tree.SharedTreeModel.BufStringDecisionPathTracker

theta - Variable in class hex.schemas.ANOVAGLMV3.ANOVAGLMParametersV3

theta - Variable in class hex.schemas.GAMV3.GAMParametersV3

theta - Variable in class hex.schemas.GLMV3.GLMParametersV3

theta - Variable in class hex.schemas.ModelSelectionV3.ModelSelectionParametersV3

ThinPlateDistanceWithKnots - Class in hex.gam.GamSplines

Implementation details of this class can be found in GamThinPlateRegressionH2O.doc attached to this GitHub issue: https://github.com/h2oai/h2o-3/issues/7783

ThinPlateDistanceWithKnots(double[][], int, double[], boolean) - Constructor for class hex.gam.GamSplines.ThinPlateDistanceWithKnots

ThinPlatePolynomialWithKnots - Class in hex.gam.GamSplines

ThinPlatePolynomialWithKnots(int, int[][], double[], double[], boolean) - Constructor for class hex.gam.GamSplines.ThinPlatePolynomialWithKnots

ThinPlateRegressionUtils - Class in hex.gam.GamSplines

This class contains functions that perform different functions for generating the thin plate regression splines and the polynomial basis functions

ThinPlateRegressionUtils() - Constructor for class hex.gam.GamSplines.ThinPlateRegressionUtils

ThinPlateRegressionUtils.ScaleTPPenalty - Class in hex.gam.GamSplines

this class performs scaling on TP penalty matrices that is done in R.

threshold - Variable in class hex.schemas.MakeGLMModelV3

thresholds - Variable in class hex.schemas.TreeV3

thresholds_x - Variable in class hex.schemas.IsotonicRegressionModelV3.IsotonicRegressionModelOutputV3

thresholds_y - Variable in class hex.schemas.IsotonicRegressionModelV3.IsotonicRegressionModelOutputV3

ties - Variable in class hex.schemas.CoxPHV3.CoxPHParametersV3

time_for_communication_us - Variable in class hex.deeplearning.DeepLearningModel

timeAverage(DeepLearningModelInfo) - Static method in class hex.deeplearning.DeepLearningModelInfo

TimeAveraging as part of Elastic Averaging Algorithm Cf.

tmat - Variable in class hex.schemas.HGLMModelV3.HGLMModelOutputV3

toAuxInfos() - Method in class hex.tree.CompressedTree

toBytes(AutoBuffer) - Method in class hex.tree.isoforextended.isolationtree.AbstractCompressedNode

Serialize Node to the byte buffer

toBytes() - Method in class hex.tree.isoforextended.isolationtree.CompressedIsolationTree

The structure of the bytes is: sizeOfInternalArrays -> size of random slope and intercept (size of both is always equal) nodeNumber -> index of the node in the array, byte arrays always starts with the root and ends with some leaf.

toBytes(AutoBuffer) - Method in class hex.tree.isoforextended.isolationtree.CompressedLeaf

The structure of the bytes is: |identifierOfTheNodeType|numRows|

toBytes(AutoBuffer) - Method in class hex.tree.isoforextended.isolationtree.CompressedNode

The structure of the bytes is: |identifierOfTheNodeType|nvalues|pvalues|

toDoubles() - Method in class hex.tree.dt.AbstractFeatureLimits

toDoubles() - Method in class hex.tree.dt.binning.AbstractBin

toDoubles() - Method in class hex.tree.dt.binning.CategoricalBin

toDoubles() - Method in class hex.tree.dt.binning.NumericBin

toDoubles() - Method in class hex.tree.dt.CategoricalFeatureLimits

toDoubles() - Method in class hex.tree.dt.DataFeaturesLimits

Serialize limits to 2D double array depending on the features types, so it can be passed to MR task

toDoubles() - Method in class hex.tree.dt.NumericFeatureLimits

toEigen - Static variable in class hex.util.LinearAlgebraUtils

toEigen(Vec) - Static method in class hex.util.LinearAlgebraUtils

toEigenArray(Vec) - Static method in class hex.util.LinearAlgebraUtils

toEigenProjectionArray(Frame, Frame, boolean) - Static method in class hex.util.LinearAlgebraUtils

toFrame(Key<Frame>) - Method in interface hex.coxph.Storage.Matrix

toFrame(Key) - Method in class hex.deeplearning.Storage.DenseColMatrix

toFrame(Key) - Method in class hex.deeplearning.Storage.DenseRowMatrix

toFrame(Key) - Method in class hex.deeplearning.Storage.DenseVector

toFrame(Key) - Method in interface hex.deeplearning.Storage.Matrix

toFrame(Key) - Method in class hex.deeplearning.Storage.SparseRowMatrix

toFrame(int, Key) - Method in interface hex.deeplearning.Storage.Tensor

toFrame(Key) - Method in interface hex.deeplearning.Storage.Vector

toFrame() - Method in class hex.word2vec.Word2VecModel

Converts this word2vec model to a Frame.

toIsotonicCalibrator() - Method in class hex.isotonic.IsotonicRegressionModel

toJavaAlgo() - Method in class hex.generic.GenericModel

toJavaCheckTooBig() - Method in class hex.deeplearning.DeepLearningModel

toJavaCheckTooBig() - Method in class hex.glm.GLMModel

toJavaCheckTooBig() - Method in class hex.kmeans.KMeansModel

toJavaCheckTooBig() - Method in class hex.tree.SharedTreePojoWriter

toJavaInit(SBPrintStream, CodeGeneratorPipeline) - Method in class hex.deeplearning.DeepLearningModel

toJavaInit(SBPrintStream, CodeGeneratorPipeline) - Method in class hex.glm.GLMModel

toJavaInit(SBPrintStream, CodeGeneratorPipeline) - Method in class hex.naivebayes.NaiveBayesModel

toJavaInit(SBPrintStream, CodeGeneratorPipeline) - Method in class hex.pca.PCAModel

toJavaInit(SBPrintStream, CodeGeneratorPipeline) - Method in class hex.svd.SVDModel

toJavaInit(SBPrintStream, CodeGeneratorPipeline) - Method in class hex.tree.SharedTreePojoWriter

toJavaModelClassName() - Method in class hex.generic.GenericModel

toJavaPredictBody(SBPrintStream, CodeGeneratorPipeline, CodeGeneratorPipeline, boolean) - Method in class hex.deeplearning.DeepLearningModel

toJavaPredictBody(SBPrintStream, CodeGeneratorPipeline, CodeGeneratorPipeline, boolean) - Method in class hex.glm.GLMModel

toJavaPredictBody(SBPrintStream, CodeGeneratorPipeline, CodeGeneratorPipeline, boolean) - Method in class hex.kmeans.KMeansModel

toJavaPredictBody(SBPrintStream, CodeGeneratorPipeline, CodeGeneratorPipeline, boolean) - Method in class hex.naivebayes.NaiveBayesModel

toJavaPredictBody(SBPrintStream, CodeGeneratorPipeline, CodeGeneratorPipeline, boolean) - Method in class hex.pca.PCAModel

toJavaPredictBody(SBPrintStream, CodeGeneratorPipeline, CodeGeneratorPipeline, boolean) - Method in class hex.svd.SVDModel

toJavaPredictBody(SBPrintStream, CodeGeneratorPipeline, CodeGeneratorPipeline, boolean) - Method in class hex.tree.SharedTreePojoWriter

toJavaTransform(SBPrintStream, CodeGeneratorPipeline, boolean) - Method in class hex.kmeans.KMeansModel

toJavaUnifyPreds(SBPrintStream) - Method in class hex.tree.SharedTreePojoWriter

toJavaUUID() - Method in class hex.generic.GenericModel

toSharedTreeSubgraph(CompressedTree, String[], String[][]) - Method in class hex.tree.CompressedTree

toString() - Method in class hex.DataInfo.Row

toString() - Method in class hex.deeplearning.DeepLearningModelInfo

Print a summary table

toString() - Method in class hex.deeplearning.Dropout

toString() - Method in class hex.deeplearning.Neurons

Print the status of this neuron layer

toString() - Method in class hex.glm.ComputationState

toString() - Method in class hex.glm.ConstrainedGLMUtils.CoefIndices

toString() - Method in class hex.glm.GLM.BetaConstraint

toString() - Method in class hex.glm.GLM.GLMGradientInfo

toString() - Method in class hex.gram.Gram

toString() - Method in class hex.hglm.HGLMModel

toString() - Method in class hex.optimization.ADMM.L1Solver

toString() - Method in class hex.optimization.L_BFGS.Result

toString() - Method in class hex.optimization.OptimizationUtils.GradientInfo

toString() - Method in class hex.optimization.OptimizationUtils.MoreThuente

toString() - Method in class hex.optimization.OptimizationUtils.SimpleBacktrackingLS

toString() - Method in class hex.psvm.MetricBuilderPSVM

toString(SharedTreeModel.SharedTreeOutput) - Method in class hex.tree.CompressedTree

toString() - Method in class hex.tree.DHistogram

toString() - Method in class hex.tree.dt.AbstractCompressedNode

toString() - Method in class hex.tree.dt.AbstractSplittingRule

toString() - Method in class hex.tree.dt.CategoricalSplittingRule

toString() - Method in class hex.tree.dt.CompressedDT

toString() - Method in class hex.tree.dt.CompressedLeaf

toString() - Method in class hex.tree.dt.CompressedNode

toString() - Method in class hex.tree.dt.NumericSplittingRule

toString() - Method in class hex.tree.DTree.DecidedNode

toString() - Method in class hex.tree.DTree.LeafNode

toString() - Method in class hex.tree.DTree.Split

toString() - Method in class hex.tree.DTree.UndecidedNode

toString() - Method in class hex.tree.TreeStats

toString2(StringBuilder, int) - Method in class hex.tree.DTree.DecidedNode

toString2(StringBuilder, int) - Method in class hex.tree.DTree.LeafNode

toString2(StringBuilder, int) - Method in class hex.tree.DTree.Node

toString2(StringBuilder, int) - Method in class hex.tree.DTree.UndecidedNode

toStringAll() - Method in class hex.deeplearning.DeepLearningModelInfo

Debugging printout

toStringTree(int, int) - Method in class hex.tree.SharedTreeModel.SharedTreeOutput

total_checkpointed_run_time_ms - Variable in class hex.deeplearning.DeepLearningModel

total_scoring_time_ms - Variable in class hex.deeplearning.DeepLearningModel

total_setup_time_ms - Variable in class hex.deeplearning.DeepLearningModel

total_training_time_ms - Variable in class hex.deeplearning.DeepLearningModel

totalBetaLength() - Method in class hex.glm.GLM.BetaInfo

totalFreeMemory() - Static method in class hex.ContributionsWithBackgroundFrameTask

toTwoDimTable(String[], String) - Method in class hex.tree.isofor.IsolationForest.VarSplits

train_samples_per_iteration - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

The number of training data rows to be processed per iteration.

training_rows - Variable in class hex.deeplearning.DeepLearningModel

training_samples - Variable in class hex.deeplearning.DeepLearningScoringInfo

training_samples() - Method in class hex.deeplearning.DeepLearningScoringInfo

trainingFrameRows - Variable in class hex.ensemble.StackedEnsembleModel

trainModel(DeepLearningModel) - Method in class hex.deeplearning.DeepLearning.DeepLearningDriver

Train a Deep Learning neural net model

trainModelImpl() - Method in class hex.adaboost.AdaBoost

trainModelImpl() - Method in class hex.aggregator.Aggregator

trainModelImpl() - Method in class hex.anovaglm.ANOVAGLM

trainModelImpl() - Method in class hex.coxph.CoxPH

trainModelImpl() - Method in class hex.deeplearning.DeepLearning

trainModelImpl() - Method in class hex.ensemble.StackedEnsemble

trainModelImpl() - Method in class hex.gam.GAM

trainModelImpl() - Method in class hex.generic.Generic

trainModelImpl() - Method in class hex.glm.GLM

trainModelImpl() - Method in class hex.glrm.GLRM

trainModelImpl() - Method in class hex.grep.Grep

trainModelImpl() - Method in class hex.hglm.HGLM

trainModelImpl() - Method in class hex.isotonic.IsotonicRegression

trainModelImpl() - Method in class hex.kmeans.KMeans

Start the KMeans training Job on an F/J thread.

trainModelImpl() - Method in class hex.modelselection.ModelSelection

trainModelImpl() - Method in class hex.naivebayes.NaiveBayes

trainModelImpl() - Method in class hex.pca.PCA

trainModelImpl() - Method in class hex.psvm.PSVM

trainModelImpl() - Method in class hex.rulefit.RuleFit

Start the KMeans training Job on an F/J thread.

trainModelImpl() - Method in class hex.svd.SVD

trainModelImpl() - Method in class hex.tree.drf.DRF

Start the DRF training Job on an F/J thread.

trainModelImpl() - Method in class hex.tree.dt.DT

trainModelImpl() - Method in class hex.tree.gbm.GBM

Start the GBM training Job on an F/J thread.

trainModelImpl() - Method in class hex.tree.isofor.IsolationForest

trainModelImpl() - Method in class hex.tree.isoforextended.ExtendedIsolationForest

trainModelImpl() - Method in class hex.tree.uplift.UpliftDRF

Start the DRF training Job on an F/J thread.

trainModelImpl() - Method in class hex.word2vec.Word2Vec

transform(int, Word2VecTransformV3) - Method in class hex.api.Word2VecHandler

transform(StackedEnsembleModel, Frame, Key<Frame>) - Method in enum hex.ensemble.StackedEnsembleModel.StackedEnsembleParameters.MetalearnerTransform

transform(double[][], double[], double[], int, int) - Static method in class hex.glrm.GLRM

transform(Frame) - Method in class hex.glrm.GLRMModel

GLRM performs the action A=X*Y during training.

transform(Frame) - Method in class hex.rulefit.RuleEnsemble

transform - Variable in class hex.schemas.AggregatorV99.AggregatorParametersV99

transform - Variable in class hex.schemas.GLRMV3.GLRMParametersV3

transform - Variable in class hex.schemas.PCAV3.PCAParametersV3

transform - Variable in class hex.schemas.SVDV99.SVDParametersV99

transform(String) - Method in class hex.word2vec.Word2VecModel

Takes an input string can return the word vector for that word.

transform(Vec, Word2VecModel.AggregateMethod) - Method in class hex.word2vec.Word2VecModel

transformInteractingPred(double[][]) - Method in class hex.anovaglm.GenerateTransformColumns

transformMultipleCols(Frame, String[][], int, String[][]) - Static method in class hex.anovaglm.ANOVAGLMUtils

transformOneCol(Frame, String) - Static method in class hex.anovaglm.ANOVAGLMUtils

perform data transformation described in AnovaGLMTutorial https://github.com/h2oai/h2o-3/issues/7561 section III.II on one predictor.

transformOneRow(double[][], double[], int, int[]) - Method in class hex.anovaglm.GenerateTransformColumns

transformTwoCols(Frame, String[], String[]) - Static method in class hex.anovaglm.ANOVAGLMUtils

Generate frame transformation on two interacting columns.

treatment_column - Variable in class hex.schemas.UpliftDRFV3.UpliftDRFParametersV3

treatmentChunkId() - Method in class hex.DataInfo

treatmentIndex - Variable in class hex.tree.SharedTree.FrameMap

tree0Index - Variable in class hex.tree.SharedTree.FrameMap

tree_class - Variable in class hex.schemas.TreeV3

tree_decision_path - Variable in class hex.schemas.TreeV3

tree_number - Variable in class hex.schemas.TreeV3

TreeHandler - Class in hex.tree

Handling requests for various model trees

TreeHandler() - Constructor for class hex.tree.TreeHandler

TreeHandler.PlainLanguageRules - Enum in hex.tree

TreeHandler.TreeProperties - Class in hex.tree

TreeMeasures(int) - Constructor for class hex.tree.drf.TreeMeasuresCollector.TreeMeasures

TreeMeasures(double[], int) - Constructor for class hex.tree.drf.TreeMeasuresCollector.TreeMeasures

TreeMeasuresCollector - Class in hex.tree.drf

Score given tree model and preserve errors per tree in form of votes (for classification) or MSE (for regression).

TreeMeasuresCollector.ShuffleTask - Class in hex.tree.drf

TreeMeasuresCollector.TreeMeasures<T extends TreeMeasuresCollector.TreeMeasures> - Class in hex.tree.drf

A simple holder for set of different tree measurements.

TreeMeasuresCollector.TreeSSE - Class in hex.tree.drf

A simple holder serving SSE per tree.

TreeMeasuresCollector.TreeVotes - Class in hex.tree.drf

A class holding tree votes.

TreeProperties() - Constructor for class hex.tree.TreeHandler.TreeProperties

TreeSSE(int) - Constructor for class hex.tree.drf.TreeMeasuresCollector.TreeSSE

TreeSSE(float[], double[], int) - Constructor for class hex.tree.drf.TreeMeasuresCollector.TreeSSE

TreeStats - Class in hex.tree

TreeStats() - Constructor for class hex.tree.TreeStats

TreeStatsV3 - Class in hex.schemas

TreeStatsV3() - Constructor for class hex.schemas.TreeStatsV3

TreeUtils - Class in hex.tree

TreeUtils() - Constructor for class hex.tree.TreeUtils

TreeV3 - Class in hex.schemas

TreeV3() - Constructor for class hex.schemas.TreeV3

TreeVisitor<T extends java.lang.Exception> - Class in hex.tree

Abstract visitor class for serialized trees.

TreeVisitor(CompressedTree) - Constructor for class hex.tree.TreeVisitor

TreeVotes(int) - Constructor for class hex.tree.drf.TreeMeasuresCollector.TreeVotes

TreeVotes(double[], double[], int) - Constructor for class hex.tree.drf.TreeMeasuresCollector.TreeVotes

TriDiagonalMatrix - Class in hex.gam.MatrixFrameUtils

TriDiagonalMatrix(int) - Constructor for class hex.gam.MatrixFrameUtils.TriDiagonalMatrix

TriDiagonalMatrix(double[]) - Constructor for class hex.gam.MatrixFrameUtils.TriDiagonalMatrix

trim(Aggregator.Exemplar[]) - Static method in class hex.aggregator.Aggregator.Exemplar

Trim any training nulls

trimTo(int) - Method in class hex.tree.SharedTreeModel.SharedTreeOutput

tweedie_epsilon - Variable in class hex.schemas.GLMV3.GLMParametersV3

tweedie_link_power - Variable in class hex.schemas.ANOVAGLMV3.ANOVAGLMParametersV3

tweedie_link_power - Variable in class hex.schemas.GAMV3.GAMParametersV3

tweedie_link_power - Variable in class hex.schemas.GLMV3.GLMParametersV3

tweedie_link_power - Variable in class hex.schemas.ModelSelectionV3.ModelSelectionParametersV3

tweedie_variance_power - Variable in class hex.schemas.ANOVAGLMV3.ANOVAGLMParametersV3

tweedie_variance_power - Variable in class hex.schemas.GAMV3.GAMParametersV3

tweedie_variance_power - Variable in class hex.schemas.GLMV3.GLMParametersV3

tweedie_variance_power - Variable in class hex.schemas.ModelSelectionV3.ModelSelectionParametersV3

TweedieEstimator - Class in hex.glm

TweedieMLDispersionOnly - Class in hex.glm

class to find bounds on infinite series approximation to calculate tweedie dispersion parameter using the maximum likelihood function in Dunn et.al.

TweedieMLDispersionOnly(Frame, GLMModel.GLMParameters, GLMModel, double[], DataInfo) - Constructor for class hex.glm.TweedieMLDispersionOnly

twoNormSq() - Method in class hex.DataInfo.Row

type - Variable in class hex.schemas.ANOVAGLMV3.ANOVAGLMParametersV3

U

u_key - Variable in class hex.schemas.SVDModelV99.SVDModelOutputV99

u_name - Variable in class hex.schemas.SVDV99.SVDParametersV99

ubeta - Variable in class hex.schemas.HGLMModelV3.HGLMModelOutputV3

undecided(int) - Method in class hex.tree.DTree

UNDECIDED_CHILD_NODE_ID - Static variable in class hex.tree.ScoreBuildHistogram

Marker for a fresh tree

UndecidedNode(DTree, int, DHistogram[], Constraints, BranchInteractionConstraints) - Constructor for class hex.tree.DTree.UndecidedNode

UndecidedNode(DTree.UndecidedNode, DTree) - Constructor for class hex.tree.DTree.UndecidedNode

unit_active(int) - Method in class hex.deeplearning.Dropout

units - Variable in class hex.deeplearning.Neurons

unScaleNumericals(double[], double[]) - Method in class hex.DataInfo

Undo the standardization/normalization of numerical columns

update(double[], double, double, int) - Method in class hex.glm.GLMModel

update(double[], double[], double, double, int) - Method in class hex.glm.GLMModel

updateAuxTreeWeights(Frame, String) - Method in class hex.tree.SharedTreeModel

updateBy(IsolationTree) - Method in class hex.tree.isoforextended.isolationtree.IsolationTreeStats

updateBy(DTree) - Method in class hex.tree.TreeStats

updateConstraintInfo(ConstrainedGLMUtils.LinearConstraints[], ConstrainedGLMUtils.LinearConstraints[]) - Method in class hex.glm.ComputationState

Any time when the glm coefficient changes, the constraints values will change and active constraints can be inactive and vice versa.

updateConstraintParameters(ComputationState, double[], double[], ConstrainedGLMUtils.LinearConstraints[], ConstrainedGLMUtils.LinearConstraints[], GLMModel.GLMParameters) - Static method in class hex.glm.ConstrainedGLMUtils

This method will update the constraint parameter values cKCS, epsilonkCS, etakCS.

updateConstraintValues(double[], List<String>, ConstrainedGLMUtils.LinearConstraints[], ConstrainedGLMUtils.LinearConstraints[]) - Static method in class hex.glm.ConstrainedGLMUtils

Simple method to all linear constraints given the coefficient values.

updateDerivativeActive(ConstrainedGLMUtils.ConstraintsDerivatives[], ConstrainedGLMUtils.ConstraintsGram[], ConstrainedGLMUtils.LinearConstraints[]) - Method in class hex.glm.ComputationState

updateDispersionP(double) - Method in class hex.glm.TweedieMLDispersionOnly

updateDOFColInfo(int, String[], int[], int[], int) - Static method in class hex.anovaglm.ANOVAGLMUtils

updateGradGam(double[], double[][][], int[][], double[], int[]) - Static method in class hex.glm.GLMUtils

updateGradGamMultinomial(double[][], double[][][], int[][], double[][]) - Static method in class hex.glm.GLMUtils

updateIVVSum(double[][], double[]) - Static method in class hex.svd.SVD

updateLambda(double[], double, ConstrainedGLMUtils.LinearConstraints[]) - Static method in class hex.glm.ConstrainedGLMUtils

updateLaterBits(int[], int[], int, int) - Static method in class hex.anovaglm.ANOVAGLMUtils

updateLaterIndices(int[], int, int) - Static method in class hex.modelselection.ModelSelectionUtils

Give 5 predictors and say we want the combo of 3 predictors, this function will properly reset the prediction combination indices say from [0, 1, 4] -> [0, 2, 3] or [0, 3, 4] -> [1, 2, 3].

updateLeafNodeWeights(double[]) - Method in class hex.tree.CompressedTree

updateMask(int, boolean[]) - Method in class hex.tree.dt.DataFeaturesLimits

Creates new instance of limits with updated mask - replaces old mask with new more precise one.

updateMaskExcluded(int, boolean[]) - Method in class hex.tree.dt.DataFeaturesLimits

Creates new instance of limits with updated mask - excludes from the current mask categories defined by the new one.

updateMax(int, double) - Method in class hex.tree.dt.DataFeaturesLimits

Creates new instance of limits with updated max.

updateMin(int, double) - Method in class hex.tree.dt.DataFeaturesLimits

Creates new instance of limits with updated min.

updateModelInfo(Word2VecModel.Word2VecModelInfo) - Method in class hex.word2vec.WordVectorTrainer

updatePredCombo(int[], int[]) - Static method in class hex.anovaglm.ANOVAGLMUtils

updatePredIndices(int[], int[]) - Static method in class hex.modelselection.ModelSelectionUtils

Given predictor indices stored in currentPredIndices, we need to find the next combination of predictor indices to use to generate the next combination.

updateProgress(boolean) - Method in class hex.glm.GLM.GLMDriver

updates - Variable in class hex.schemas.GLRMModelV3.GLRMModelOutputV3

updateState(double[], double) - Method in class hex.glm.ComputationState

updateState(double[], GLM.GLMGradientInfo) - Method in class hex.glm.ComputationState

updateSubmodel(int, GLMModel.Submodel) - Method in class hex.glm.GLMModel

updateTweedieParams(double, double, double) - Method in class hex.glm.GLMModel.GLMParameters

updateWeightedSigmaAndMean(double[], double[]) - Method in class hex.DataInfo

updateWeightedSigmaAndMeanForResponse(double[], double[]) - Method in class hex.DataInfo

updateXVecs(int, int) - Constructor for class hex.glrm.GLRM.updateXVecs

uplift_metric - Variable in class hex.schemas.UpliftDRFV3.UpliftDRFParametersV3

UpliftDRF - Class in hex.tree.uplift

UpliftDRF(UpliftDRFModel.UpliftDRFParameters) - Constructor for class hex.tree.uplift.UpliftDRF

UpliftDRF(UpliftDRFModel.UpliftDRFParameters, Key<UpliftDRFModel>) - Constructor for class hex.tree.uplift.UpliftDRF

UpliftDRF(UpliftDRFModel.UpliftDRFParameters, Job) - Constructor for class hex.tree.uplift.UpliftDRF

UpliftDRF(boolean) - Constructor for class hex.tree.uplift.UpliftDRF

UpliftDRF.UpliftMetricType - Enum in hex.tree.uplift

UpliftDRFModel - Class in hex.tree.uplift

UpliftDRFModel(Key<UpliftDRFModel>, UpliftDRFModel.UpliftDRFParameters, UpliftDRFModel.UpliftDRFOutput) - Constructor for class hex.tree.uplift.UpliftDRFModel

UpliftDRFModel.UpliftDRFOutput - Class in hex.tree.uplift

UpliftDRFModel.UpliftDRFParameters - Class in hex.tree.uplift

UpliftDRFModel.UpliftDRFParameters.UpliftMetricType - Enum in hex.tree.uplift

UpliftDRFModelOutputV3() - Constructor for class hex.schemas.UpliftDRFModelV3.UpliftDRFModelOutputV3

UpliftDRFModelV3 - Class in hex.schemas

UpliftDRFModelV3() - Constructor for class hex.schemas.UpliftDRFModelV3

UpliftDRFModelV3.UpliftDRFModelOutputV3 - Class in hex.schemas

UpliftDrfMojoWriter - Class in hex.tree.uplift

UpliftDrfMojoWriter() - Constructor for class hex.tree.uplift.UpliftDrfMojoWriter

UpliftDrfMojoWriter(UpliftDRFModel) - Constructor for class hex.tree.uplift.UpliftDrfMojoWriter

UpliftDRFOutput(UpliftDRF) - Constructor for class hex.tree.uplift.UpliftDRFModel.UpliftDRFOutput

UpliftDRFParameters() - Constructor for class hex.tree.uplift.UpliftDRFModel.UpliftDRFParameters

UpliftDRFParametersV3() - Constructor for class hex.schemas.UpliftDRFV3.UpliftDRFParametersV3

UpliftDRFV3 - Class in hex.schemas

UpliftDRFV3() - Constructor for class hex.schemas.UpliftDRFV3

UpliftDRFV3.UpliftDRFParametersV3 - Class in hex.schemas

upliftGain() - Method in class hex.tree.DTree.Split

use_all - Variable in class hex.schemas.DataInfoFrameV3

use_all_factor_levels - Variable in class hex.schemas.AggregatorV99.AggregatorParametersV99

use_all_factor_levels - Variable in class hex.schemas.CoxPHV3.CoxPHParametersV3

use_all_factor_levels - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

use_all_factor_levels - Variable in class hex.schemas.GramV3

use_all_factor_levels - Variable in class hex.schemas.PCAV3.PCAParametersV3

use_all_factor_levels - Variable in class hex.schemas.SVDV99.SVDParametersV99

useBounds() - Method in class hex.tree.Constraints

useColSampling() - Method in class hex.tree.gbm.GBMModel.GBMParameters

useColSampling() - Method in class hex.tree.SharedTreeModel.SharedTreeParameters

useIntOpt(Vec, SharedTreeModel.SharedTreeParameters, Constraints) - Static method in class hex.tree.DHistogram

Determines if histogram making can use integer optimization when extracting data.

user_points - Variable in class hex.schemas.KMeansV3.KMeansParametersV3

user_x - Variable in class hex.schemas.GLRMV3.GLRMParametersV3

user_y - Variable in class hex.schemas.GLRMV3.GLRMParametersV3

useRowSampling() - Method in class hex.tree.SharedTreeModel.SharedTreeParameters

V

v_key - Variable in class hex.schemas.SVDModelV99.SVDModelOutputV99

validate(GLM) - Method in class hex.glm.GLMModel.GLMParameters

validate(RuleFit) - Method in class hex.rulefit.RuleFitModel.RuleFitParameters

validateBinaryResponse() - Method in class hex.coxph.CoxPH

validateParams(P) - Method in class hex.ensemble.Metalearner

validateRowSampleRate() - Method in class hex.tree.isofor.IsolationForest

validateRowSampleRate() - Method in class hex.tree.SharedTree

validateStoppingMetric() - Method in class hex.tree.isofor.IsolationForest

validation_response_column - Variable in class hex.schemas.IsolationForestV3.IsolationForestParametersV3

validation_rows - Variable in class hex.deeplearning.DeepLearningModel

validDinfo(Frame) - Method in class hex.DataInfo

validWorkspace() - Method in class hex.tree.SharedTree

value() - Method in enum hex.tree.DHistogram.NASplitDir

value(double, double, double, double, double, double, double, double, double, double, double, double) - Method in class hex.tree.uplift.Divergence

Calculate normalized gain as result value to select best split.

valueOf(String) - Static method in enum hex.adaboost.AdaBoostModel.Algorithm

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum hex.coxph.CoxPHModel.CoxPHParameters.CoxPHTies

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum hex.DataInfo.TransformType

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum hex.deeplearning.DeepLearningModel.DeepLearningParameters.Activation

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum hex.deeplearning.DeepLearningModel.DeepLearningParameters.ClassSamplingMethod

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum hex.deeplearning.DeepLearningModel.DeepLearningParameters.InitialWeightDistribution

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum hex.deeplearning.DeepLearningModel.DeepLearningParameters.Loss

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum hex.deeplearning.DeepLearningModel.DeepLearningParameters.MissingValuesHandling

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum hex.ensemble.Metalearner.Algorithm

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum hex.ensemble.StackedEnsembleModel.StackedEnsembleParameters.MetalearnerTransform

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum hex.ensemble.StackedEnsembleModel.StackingStrategy

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum hex.gam.MatrixFrameUtils.GamUtils.AllocateType

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum hex.glm.DispersionTask.ConstColNames

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum hex.glm.DispersionTask.InfoColNames

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum hex.glm.GLMModel.GLMParameters.Constraints

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum hex.glm.GLMModel.GLMParameters.DispersionMethod

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum hex.glm.GLMModel.GLMParameters.Family

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum hex.glm.GLMModel.GLMParameters.GLMType

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum hex.glm.GLMModel.GLMParameters.Influence

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum hex.glm.GLMModel.GLMParameters.Link

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum hex.glm.GLMModel.GLMParameters.MissingValuesHandling

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum hex.glm.GLMModel.GLMParameters.Solver

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum hex.hglm.HGLMModel.HGLMParameters.Method

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum hex.isotonic.IsotonicRegressionModel.OutOfBoundsHandling

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum hex.kmeans.KMeans.Initialization

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum hex.modelselection.ModelSelectionModel.ModelSelectionParameters.Mode

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum hex.pca.PCAImplementation

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum hex.pca.PCAModel.PCAParameters.Method

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum hex.rulefit.Condition.Operator

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum hex.rulefit.Condition.Type

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum hex.rulefit.RuleFitModel.Algorithm

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum hex.rulefit.RuleFitModel.ModelType

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum hex.svd.SVDModel.SVDParameters.Method

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum hex.tree.CalibrationHelper.CalibrationMethod

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum hex.tree.DHistogram.NASplitDir

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum hex.tree.dt.binning.BinningStrategy

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum hex.tree.SharedTreeModel.SharedTreeParameters.HistogramType

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum hex.tree.TreeHandler.PlainLanguageRules

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum hex.tree.uplift.UpliftDRF.UpliftMetricType

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum hex.tree.uplift.UpliftDRFModel.UpliftDRFParameters.UpliftMetricType

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum hex.word2vec.Word2Vec.NormModel

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum hex.word2vec.Word2Vec.WordModel

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum hex.word2vec.Word2VecModel.AggregateMethod

Returns the enum constant of this type with the specified name.

values() - Static method in enum hex.adaboost.AdaBoostModel.Algorithm

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum hex.coxph.CoxPHModel.CoxPHParameters.CoxPHTies

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum hex.DataInfo.TransformType

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum hex.deeplearning.DeepLearningModel.DeepLearningParameters.Activation

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum hex.deeplearning.DeepLearningModel.DeepLearningParameters.ClassSamplingMethod

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum hex.deeplearning.DeepLearningModel.DeepLearningParameters.InitialWeightDistribution

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum hex.deeplearning.DeepLearningModel.DeepLearningParameters.Loss

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum hex.deeplearning.DeepLearningModel.DeepLearningParameters.MissingValuesHandling

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum hex.ensemble.Metalearner.Algorithm

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum hex.ensemble.StackedEnsembleModel.StackedEnsembleParameters.MetalearnerTransform

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum hex.ensemble.StackedEnsembleModel.StackingStrategy

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum hex.gam.MatrixFrameUtils.GamUtils.AllocateType

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum hex.glm.DispersionTask.ConstColNames

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum hex.glm.DispersionTask.InfoColNames

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum hex.glm.GLMModel.GLMParameters.Constraints

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum hex.glm.GLMModel.GLMParameters.DispersionMethod

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum hex.glm.GLMModel.GLMParameters.Family

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum hex.glm.GLMModel.GLMParameters.GLMType

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum hex.glm.GLMModel.GLMParameters.Influence

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum hex.glm.GLMModel.GLMParameters.Link

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum hex.glm.GLMModel.GLMParameters.MissingValuesHandling

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum hex.glm.GLMModel.GLMParameters.Solver

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum hex.hglm.HGLMModel.HGLMParameters.Method

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum hex.isotonic.IsotonicRegressionModel.OutOfBoundsHandling

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum hex.kmeans.KMeans.Initialization

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum hex.modelselection.ModelSelectionModel.ModelSelectionParameters.Mode

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum hex.pca.PCAImplementation

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum hex.pca.PCAModel.PCAParameters.Method

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum hex.rulefit.Condition.Operator

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum hex.rulefit.Condition.Type

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum hex.rulefit.RuleFitModel.Algorithm

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum hex.rulefit.RuleFitModel.ModelType

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum hex.svd.SVDModel.SVDParameters.Method

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum hex.tree.CalibrationHelper.CalibrationMethod

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum hex.tree.DHistogram.NASplitDir

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum hex.tree.dt.binning.BinningStrategy

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum hex.tree.SharedTreeModel.SharedTreeParameters.HistogramType

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum hex.tree.TreeHandler.PlainLanguageRules

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum hex.tree.uplift.UpliftDRF.UpliftMetricType

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum hex.tree.uplift.UpliftDRFModel.UpliftDRFParameters.UpliftMetricType

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum hex.word2vec.Word2Vec.NormModel

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum hex.word2vec.Word2Vec.WordModel

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum hex.word2vec.Word2VecModel.AggregateMethod

Returns an array containing the constants of this enum type, in the order they are declared.

var(int) - Method in class hex.tree.DHistogram

compute the sample variance within a given bin

variable_importances - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3

Whether to compute variable importances for input features.

variable_splits - Variable in class hex.schemas.IsolationForestModelV3.IsolationForestModelOutputV3

variableInflationFactors() - Method in class hex.glm.GLMModel.GLMOutput

variance(double) - Method in class hex.glm.GLMModel.GLMParameters

variance(double) - Method in class hex.glm.GLMModel.GLMWeightsFun

varImp() - Method in class hex.deeplearning.DeepLearningModel

vcov() - Method in class hex.glm.GLMModel.GLMOutput

Variance Covariance matrix accessor.

vec_nids(Frame, int) - Method in class hex.tree.SharedTree

vec_offset(Frame) - Method in class hex.tree.SharedTree

vec_oobt(Frame) - Method in class hex.tree.SharedTree

vec_resp(Frame) - Method in class hex.tree.SharedTree

vec_size - Variable in class hex.schemas.Word2VecV3.Word2VecParametersV3

vec_tree(Frame, int) - Method in class hex.tree.SharedTree

vec_weight(Frame) - Method in class hex.tree.SharedTree

vec_work(Frame, int) - Method in class hex.tree.SharedTree

vectors_frame - Variable in class hex.schemas.Word2VecTransformV3

visit() - Method in class hex.tree.TreeVisitor

votes() - Method in class hex.tree.drf.TreeMeasuresCollector.TreeVotes

Returns number of positive votes per tree.

W

w - Variable in class hex.glm.GLMModel.GLMWeights

W - Variable in class hex.schemas.GramV3

w(int) - Method in class hex.tree.DHistogram

water.api - package water.api

water.rapids.prims - package water.rapids.prims

water.rapids.prims.isotonic - package water.rapids.prims.isotonic

water.rapids.prims.rulefit - package water.rapids.prims.rulefit

water.rapids.prims.tree - package water.rapids.prims.tree

water.rapids.prims.word2vec - package water.rapids.prims.word2vec

water.tools - package water.tools

weak_learner - Variable in class hex.schemas.AdaBoostV3.AdaBoostParametersV3

weak_learner_params - Variable in class hex.schemas.AdaBoostV3.AdaBoostParametersV3

weight - Variable in class hex.DataInfo.Row

weightChunkId() - Method in class hex.DataInfo

WEIGHTIND - Static variable in class hex.glm.DispersionTask

weightIndex - Variable in class hex.tree.SharedTree.FrameMap

weightsIdx() - Method in class hex.coxph.CoxPHModel.CoxPHOutput

window_size - Variable in class hex.schemas.Word2VecV3.Word2VecParametersV3

wNA() - Method in class hex.tree.DHistogram

word - Variable in class hex.schemas.Word2VecSynonymsV3

Word2Vec - Class in hex.word2vec

Word2Vec(boolean) - Constructor for class hex.word2vec.Word2Vec

Word2Vec(Word2VecModel.Word2VecParameters) - Constructor for class hex.word2vec.Word2Vec

Word2Vec.NormModel - Enum in hex.word2vec

Word2Vec.WordModel - Enum in hex.word2vec

Word2VecHandler - Class in hex.api

Word2VecHandler() - Constructor for class hex.api.Word2VecHandler

Word2VecModel - Class in hex.word2vec

Word2VecModel(Key<Word2VecModel>, Word2VecModel.Word2VecParameters, Word2VecModel.Word2VecOutput) - Constructor for class hex.word2vec.Word2VecModel

Word2VecModel.AggregateMethod - Enum in hex.word2vec

Word2VecModel.Vocabulary - Class in hex.word2vec

Word2VecModel.Word2VecModelInfo - Class in hex.word2vec

Word2VecModel.Word2VecOutput - Class in hex.word2vec

Word2VecModel.Word2VecParameters - Class in hex.word2vec

Word2VecModel.WordCounts - Class in hex.word2vec

Word2VecModelInfo() - Constructor for class hex.word2vec.Word2VecModel.Word2VecModelInfo

Word2VecModelOutputV3() - Constructor for class hex.schemas.Word2VecModelV3.Word2VecModelOutputV3

Word2VecModelV3 - Class in hex.schemas

Word2VecModelV3() - Constructor for class hex.schemas.Word2VecModelV3

Word2VecModelV3.Word2VecModelOutputV3 - Class in hex.schemas

Word2VecMojoWriter - Class in hex.word2vec

MOJO serializer for word2vec model.

Word2VecMojoWriter() - Constructor for class hex.word2vec.Word2VecMojoWriter

Word2VecMojoWriter(Word2VecModel) - Constructor for class hex.word2vec.Word2VecMojoWriter

Word2VecOutput(Word2Vec) - Constructor for class hex.word2vec.Word2VecModel.Word2VecOutput

Word2VecParameters() - Constructor for class hex.word2vec.Word2VecModel.Word2VecParameters

Word2VecParametersV3() - Constructor for class hex.schemas.Word2VecV3.Word2VecParametersV3

Word2VecSynonymsV3 - Class in hex.schemas

Word2VecSynonymsV3() - Constructor for class hex.schemas.Word2VecSynonymsV3

Word2VecTransformV3 - Class in hex.schemas

Word2VecTransformV3() - Constructor for class hex.schemas.Word2VecTransformV3

Word2VecV3 - Class in hex.schemas

Word2VecV3() - Constructor for class hex.schemas.Word2VecV3

Word2VecV3.Word2VecParametersV3 - Class in hex.schemas

word_model - Variable in class hex.schemas.Word2VecV3.Word2VecParametersV3

WordCountTask - Class in hex.word2vec

Reduce a string column of a given Vec to a set of unique words and their frequency counts Currently the array is consolidated on the calling node.

words_frame - Variable in class hex.schemas.Word2VecTransformV3

WordVectorConverter - Class in hex.word2vec

WordVectorConverter(Job<Word2VecModel>, int, int) - Constructor for class hex.word2vec.WordVectorConverter

WordVectorTrainer - Class in hex.word2vec

WordVectorTrainer(Job<Word2VecModel>, Word2VecModel.Word2VecModelInfo) - Constructor for class hex.word2vec.WordVectorTrainer

work0Index - Variable in class hex.tree.SharedTree.FrameMap

WORK_TOTAL - Static variable in class hex.glm.GLM

WORK_TOTAL - Static variable in class hex.rulefit.RuleFit

write_impl(AutoBuffer) - Method in class hex.coxph.CoxPHModel.FrameMatrix

write_impl(AutoBuffer) - Method in class hex.word2vec.WordCountTask

writeAll_impl(AutoBuffer) - Method in class hex.adaboost.AdaBoostModel

writeAll_impl(AutoBuffer) - Method in class hex.anovaglm.ANOVAGLMModel

writeAll_impl(AutoBuffer) - Method in class hex.ensemble.StackedEnsembleModel

Write out models (base + metalearner)

writeAll_impl(AutoBuffer) - Method in class hex.gam.GAMModel

writeAll_impl(AutoBuffer) - Method in class hex.glm.GLMModel

writeAll_impl(AutoBuffer) - Method in class hex.glrm.GLRMModel

writeAll_impl(AutoBuffer) - Method in class hex.hglm.HGLMModel

writeAll_impl(AutoBuffer) - Method in class hex.modelselection.ModelSelectionModel

writeAll_impl(AutoBuffer) - Method in class hex.svd.SVDModel

Write out K/V pairs

writeAll_impl(AutoBuffer) - Method in class hex.tree.dt.DTModel

writeAll_impl(AutoBuffer) - Method in class hex.tree.isoforextended.ExtendedIsolationForestModel

writeAll_impl(AutoBuffer) - Method in class hex.tree.SharedTreeModel

Write out K/V pairs

writeModelData() - Method in class hex.coxph.CoxPHMojoWriter

writeModelData() - Method in class hex.deeplearning.DeepLearningMojoWriter

writeModelData() - Method in class hex.gam.GAMMojoWriter

writeModelData() - Method in class hex.generic.GenericModelMojoWriter

writeModelData() - Method in class hex.glm.GLMMojoWriter

writeModelData() - Method in class hex.glrm.GlrmMojoWriter

writeModelData() - Method in class hex.isotonic.IsotonicRegressionMojoWriter

writeModelData() - Method in class hex.kmeans.KMeansMojoWriter

writeModelData() - Method in class hex.pca.PCAMojoWriter

writeModelData() - Method in class hex.tree.drf.DrfMojoWriter

writeModelData() - Method in class hex.tree.gbm.GbmMojoWriter

writeModelData() - Method in class hex.tree.isofor.IsolationForestMojoWriter

writeModelData() - Method in class hex.tree.isoforextended.ExtendedIsolationForestMojoWriter

writeModelData() - Method in class hex.tree.SharedTreeMojoWriter

writeModelData() - Method in class hex.tree.uplift.UpliftDrfMojoWriter

writeModelData() - Method in class hex.word2vec.Word2VecMojoWriter

writeParentModelData() - Method in class hex.ensemble.StackedEnsembleMojoWriter

writeParentModelData() - Method in class hex.rulefit.RuleFitMojoWriter

writeTo(OutputStream, StreamWriteOption...) - Method in class hex.generic.GenericModelMojoWriter

wsum() - Method in class hex.glm.GLMTask.YMUTask

wY(int) - Method in class hex.tree.DHistogram

wYNA() - Method in class hex.tree.DHistogram

wYY(int) - Method in class hex.tree.DHistogram

wYYNA() - Method in class hex.tree.DHistogram

X

X - Variable in class hex.schemas.GramV3

xFrameVec(Chunk[], int, int) - Static method in class hex.glrm.GLRM

xy - Variable in class hex.glm.ComputationState.GramXY

Y

yArcheTypeVal(GLRM.Archetypes, int, int) - Static method in class hex.glrm.GLRM

ymu() - Method in class hex.glm.GLMModel.GLMOutput

YMUTask(DataInfo, int, boolean, boolean, boolean, boolean) - Constructor for class hex.glm.GLMTask.YMUTask

yy - Variable in class hex.glm.ComputationState.GramXY

Z

z - Variable in class hex.glm.GLMModel.GLMWeights

z_values - Variable in class hex.schemas.GLMRegularizationPathV3

ZERO_TO_DIVIDE - Static variable in class hex.tree.uplift.Divergence

zeroOutIStranspose(int[], double[][][]) - Static method in class hex.gam.MatrixFrameUtils.GAMModelUtils

zValues() - Method in class hex.glm.ComputationState

zValues() - Method in class hex.glm.GLMModel.GLMOutput

zValues - Variable in class hex.glm.GLMModel.Submodel

zValues() - Method in class hex.glm.GLMModel.Submodel

_

_a - Variable in class hex.deeplearning.Neurons

_abAux - Variable in class hex.tree.DTree

_absoluteSplitPts - Variable in class hex.tree.DHistogram

_activation - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

The activation function (non-linearity) to be used the neurons in the hidden layers.

_active - Variable in class hex.glm.ConstrainedGLMUtils.ConstraintsDerivatives

_active - Variable in class hex.glm.ConstrainedGLMUtils.ConstraintsGram

_active - Variable in class hex.glm.ConstrainedGLMUtils.LinearConstraints

_activeCols - Variable in class hex.DataInfo

_activeColsPerClass - Variable in class hex.glm.GLMModel.GLMOutput

_activeDataMultinomial - Variable in class hex.glm.ComputationState

_adaptedFrame - Variable in class hex.DataInfo

_adaptive_rate - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

The implemented adaptive learning rate algorithm (ADADELTA) automatically combines the benefits of learning rate annealing and momentum training to avoid slow convergence.

_afjtafj - Variable in class hex.hglm.HGLMModel.HGLMModelOutput

_AfjTAfj - Variable in class hex.hglm.HGLMTask.ComputationEngineTask

_afjtarj - Variable in class hex.hglm.HGLMModel.HGLMModelOutput

_AfjTArj - Variable in class hex.hglm.HGLMTask.ComputationEngineTask

_afjtyj - Variable in class hex.hglm.HGLMModel.HGLMModelOutput

_AfjTYj - Variable in class hex.hglm.HGLMTask.ComputationEngineTask

_AfjTYjSum - Variable in class hex.hglm.HGLMTask.ComputationEngineTask

_AfTAftInv - Variable in class hex.hglm.HGLMTask.ComputationEngineTask

_AfTAftInvAfjTYj - Variable in class hex.hglm.HGLMTask.ComputationEngineTask

_aggSplitRatios - Variable in class hex.tree.isofor.IsolationForest.VarSplits

_algorithm - Variable in class hex.rulefit.RuleFitModel.RuleFitParameters

_all_constraints_satisfied - Variable in class hex.glm.GLMModel.GLMOutput

_alpha - Variable in class hex.anovaglm.ANOVAGLMModel.ANOVAGLMParameters

_alpha - Variable in class hex.gam.GAMModel.GAMParameters

_alpha - Variable in class hex.glm.GLMModel.GLMParameters

_alpha - Variable in class hex.modelselection.ModelSelectionModel.ModelSelectionParameters

_alpha_key - Variable in class hex.psvm.PSVMModel.PSVMModelOutput

_alphai - Variable in class hex.optimization.OptimizationUtils.ExactLineSearch

_alphal - Variable in class hex.optimization.OptimizationUtils.ExactLineSearch

_alphar - Variable in class hex.optimization.OptimizationUtils.ExactLineSearch

_alphas - Variable in class hex.glm.GLMModel.RegularizationPath

_apriori - Variable in class hex.naivebayes.NaiveBayesModel.NaiveBayesOutput

_apriori_raw - Variable in class hex.naivebayes.NaiveBayesModel.NaiveBayesOutput

_archetypes - Variable in class hex.glrm.GLRMModel.GLRMOutput

_archetypes_raw - Variable in class hex.glrm.GLRMModel.GLRMOutput

_ArjTAfj - Variable in class hex.hglm.HGLMTask.ComputationEngineTask

_arjtarj - Variable in class hex.hglm.HGLMModel.HGLMModelOutput

_ArjTArj - Variable in class hex.hglm.HGLMTask.ComputationEngineTask

_arjtyj - Variable in class hex.hglm.HGLMModel.HGLMModelOutput

_ArjTYj - Variable in class hex.hglm.HGLMTask.ComputationEngineTask

_atq - Variable in class hex.util.LinearAlgebraUtils.SMulTask

_auc - Variable in class hex.psvm.MetricBuilderPSVM

_autoencoder - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

_average_activation - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

_avg_a - Variable in class hex.deeplearning.Neurons

_avg_change_obj - Variable in class hex.glrm.GLRMModel.GLRMOutput

_b - Variable in class hex.deeplearning.Neurons

_base_model_predictions_keys - Variable in class hex.ensemble.StackedEnsembleModel.StackedEnsembleOutput

_base_models - Variable in class hex.ensemble.StackedEnsembleModel.StackedEnsembleParameters

_bEA - Variable in class hex.deeplearning.Neurons

_best_alpha - Variable in class hex.gam.GAMModel.GAMModelOutput

_best_lambda - Variable in class hex.gam.GAMModel.GAMModelOutput

_best_lambda_idx - Variable in class hex.glm.GLMModel.GLMOutput

_best_model_ids - Variable in class hex.modelselection.ModelSelectionModel.ModelSelectionModelOutput

_best_submodel_idx - Variable in class hex.glm.GLMModel.GLMOutput

_bestModelPredictors - Variable in class hex.modelselection.ModelSelection

_bestR2Values - Variable in class hex.modelselection.ModelSelection

_beta - Variable in class hex.hglm.ComputationStateHGLM.ComputationStateSimple

_beta - Variable in class hex.hglm.HGLMModel.HGLMModelOutput

_beta - Variable in class hex.hglm.HGLMTask.ResidualLLHTask

_beta - Variable in class hex.hglm.MetricBuilderHGLM

_beta_constraints - Variable in class hex.gam.GAMModel.GAMParameters

_beta_constraints - Variable in class hex.glm.GLMModel.GLMParameters

_beta_epsilon - Variable in class hex.gam.GAMModel.GAMParameters

_beta_epsilon - Variable in class hex.glm.GLMModel.GLMParameters

_beta_epsilon - Variable in class hex.modelselection.ModelSelectionModel.ModelSelectionParameters

_betaCndCheckpoint - Variable in class hex.glm.GLMModel

_betaConstraintsOff - Variable in class hex.gam.GAMModel.GAMParameters

_betadiff_var - Variable in class hex.glm.GLMModel.GLMOutput

_betaInfo - Variable in class hex.glm.GLM

_betaLenPerClass - Variable in class hex.glm.GLM.BetaInfo

_betaLS1 - Variable in class hex.optimization.OptimizationUtils.ExactLineSearch

_betaLS2 - Variable in class hex.optimization.OptimizationUtils.ExactLineSearch

_betweenss - Variable in class hex.kmeans.KMeansModel.KMeansOutput

_bics - Variable in class hex.tree.DTree.UndecidedNode

_bin - Variable in class hex.tree.DTree.Split

_binomial - Variable in class hex.glm.GLMModel.GLMOutput

_binomial_double_trees - Variable in class hex.tree.drf.DRFModel.DRFParameters

_binomialOpt - Variable in class hex.tree.SharedTreePojoWriter

_bins - Variable in class hex.tree.dt.mrtasks.CountBinsSamplesCountsMRTask

_binvD - Variable in class hex.gam.GAMModel.GAMModelOutput

_bInvD - Variable in class hex.gam.MatrixFrameUtils.GenCSSplineGamOneColumn

_blending - Variable in class hex.ensemble.StackedEnsembleModel.StackedEnsembleParameters

_bs - Variable in class hex.gam.GAMModel.GAMParameters

_bs_sorted - Variable in class hex.gam.GAMModel.GAMParameters

_bsv_count - Variable in class hex.psvm.PSVMModel.PSVMModelOutput

_build_glm_model - Variable in class hex.modelselection.ModelSelectionModel.ModelSelectionParameters

_build_null_model - Variable in class hex.glm.GLMModel.GLMParameters

_build_tree_one_node - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters

_byte_size - Variable in class hex.tree.TreeStats

_c_neg - Variable in class hex.psvm.psvm.PrimalDualIPM.Parms

_c_pos - Variable in class hex.psvm.psvm.PrimalDualIPM.Parms

_calc_cumhaz - Variable in class hex.coxph.CoxPHModel.CoxPHParameters

_calc_like - Variable in class hex.glm.GLMModel.GLMParameters

_calib_model - Variable in class hex.tree.SharedTreeModel.SharedTreeOutput

_calibrate_model - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters

_calibration_frame - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters

_calibration_method - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters

_catcnt - Variable in class hex.glrm.ModelMetricsGLRM

_catcnt - Variable in class hex.glrm.ModelMetricsGLRM.GlrmModelMetricsBuilder

_categorical_column_count - Variable in class hex.kmeans.KMeansModel.KMeansOutput

_category - Variable in class hex.tree.dt.binning.CategoricalBin

_caterr - Variable in class hex.glrm.ModelMetricsGLRM

_catLvls - Variable in class hex.DataInfo

_catMissing - Variable in class hex.DataInfo

_catNAFills - Variable in class hex.anovaglm.GenerateTransformColumns

_catOffsets - Variable in class hex.DataInfo

_catOffsets - Variable in class hex.glrm.GLRMModel.GLRMOutput

_catOffsets - Variable in class hex.pca.PCAModel.PCAOutput

_catOffsets - Variable in class hex.svd.SVDModel.SVDOutput

_catOffsets - Variable in class hex.tree.SharedTreeModelWithContributions.ScoreContributionsWithBackgroundTask

_cats - Variable in class hex.DataInfo

_cforest - Variable in class hex.tree.DTreeScorer

_checkConstraintConsistency - Variable in class hex.tree.DTree

_checkFloatSplits - Variable in class hex.tree.DHistogram

_classification_stop - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

The stopping criteria in terms of classification error (1-accuracy) on the training data scoring dataset.

_cluster_size_constraints - Variable in class hex.kmeans.KMeansModel.KMeansParameters

_coef - Variable in class hex.coxph.CoxPHModel.CoxPHOutput

_coef_names - Variable in class hex.coxph.CoxPHModel.CoxPHOutput

_coefficient_names - Variable in class hex.anovaglm.ANOVAGLMModel.ANOVAGLMModelOutput

_coefficient_names - Variable in class hex.gam.GAMModel.GAMModelOutput

_coefficient_names - Variable in class hex.glm.GLMModel.GLMOutput

_coefficient_names - Variable in class hex.glm.GLMModel.RegularizationPath

_coefficient_names_no_centering - Variable in class hex.gam.GAMModel.GAMModelOutput

_coefficients - Variable in class hex.glm.GLMModel.RegularizationPath

_coefficients_std - Variable in class hex.glm.GLMModel.RegularizationPath

_coefficients_table - Variable in class hex.anovaglm.ANOVAGLMModel.ANOVAGLMModelOutput

_coefficients_table - Variable in class hex.gam.GAMModel.GAMModelOutput

_coefficients_table_no_centering - Variable in class hex.gam.GAMModel.GAMModelOutput

_coeffNames - Variable in class hex.optimization.OptimizationUtils.ExactLineSearch

_coeffs - Variable in class hex.gam.GamSplines.NBSplinesTypeIDerivative

_coefIndicesValue - Variable in class hex.glm.ConstrainedGLMUtils.ConstraintsGram

_coefNames - Variable in class hex.DataInfo

_coefOriginalIndices - Variable in class hex.DataInfo

_col - Variable in class hex.tree.DTree.Split

_col_major - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

_col_sample_rate - Variable in class hex.tree.gbm.GBMModel.GBMParameters

_col_sample_rate_change_per_level - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters

_col_sample_rate_per_tree - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters

_cold_start - Variable in class hex.gam.GAMModel.GAMParameters

_cold_start - Variable in class hex.glm.GLMModel.GLMParameters

_cols - Variable in class hex.tree.DTree

_compressed_svs - Variable in class hex.psvm.PSVMModel.PSVMModelOutput

_compute_metrics - Variable in class hex.naivebayes.NaiveBayesModel.NaiveBayesParameters

_compute_metrics - Variable in class hex.pca.PCAModel.PCAParameters

_compute_p_values - Variable in class hex.anovaglm.ANOVAGLMModel.ANOVAGLMParameters

_compute_p_values - Variable in class hex.gam.GAMModel.GAMParameters

_compute_p_values - Variable in class hex.glm.GLMModel.GLMParameters

_compute_p_values - Variable in class hex.modelselection.ModelSelectionModel.ModelSelectionParameters

_constantTerms - Variable in class hex.gam.GamSplines.ThinPlateDistanceWithKnots

_constraint_alpha - Variable in class hex.glm.GLMModel.GLMParameters

_constraint_beta - Variable in class hex.glm.GLMModel.GLMParameters

_constraint_c0 - Variable in class hex.glm.GLMModel.GLMParameters

_constraint_eta0 - Variable in class hex.glm.GLMModel.GLMParameters

_constraint_tau - Variable in class hex.glm.GLMModel.GLMParameters

_constraintCoefficientNames - Variable in class hex.glm.GLMModel.GLMOutput

_constraints - Variable in class hex.glm.ConstrainedGLMUtils.LinearConstraints

_constraintsDerivative - Variable in class hex.glm.ConstrainedGLMUtils.ConstraintsDerivatives

_constraintsVal - Variable in class hex.glm.ConstrainedGLMUtils.LinearConstraints

_contamination - Variable in class hex.tree.isofor.IsolationForestModel.IsolationForestParameters

_count - Variable in class hex.tree.dt.binning.AbstractBin

_count0 - Variable in class hex.tree.dt.binning.AbstractBin

_counts - Variable in class hex.aggregator.AggregatorModel

_countsByClass - Variable in class hex.tree.dt.mrtasks.GetClassCountsMRTask

_criterionValue - Variable in class hex.tree.dt.AbstractSplittingRule

_cs - Variable in class hex.tree.DTree.UndecidedNode

_csGLMState - Variable in class hex.glm.ComputationState

_ct - Variable in class hex.tree.TreeVisitor

_cubicSplineNum - Variable in class hex.gam.GAMModel

_currGradDirIP - Variable in class hex.optimization.OptimizationUtils.ExactLineSearch

_d - Variable in class hex.svd.SVDModel.SVDOutput

_debugTDispersionOnly - Variable in class hex.glm.GLMModel.GLMParameters

_decisionPaths - Variable in class hex.tree.TreeHandler.TreeProperties

_defaultAuucThresholds - Variable in class hex.tree.uplift.UpliftDRFModel.UpliftDRFOutput

_defaultThreshold - Variable in class hex.generic.GenericModelOutput

_depth - Variable in class hex.tree.DTree

_depth - Variable in class hex.tree.TreeVisitor

_descriptions - Variable in class hex.tree.TreeHandler.TreeProperties

_devianceTrain - Variable in class hex.gam.GAMModel.GAMModelOutput

_devianceValid - Variable in class hex.gam.GAMModel.GAMModelOutput

_diag - Variable in class hex.gram.Gram

_diag - Variable in class hex.gram.Gram.Cholesky

_diagAdded - Variable in class hex.gram.Gram

_diagN - Variable in class hex.gram.Gram

_diagnostics - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

Gather diagnostics for hidden layers, such as mean and RMS values of learning rate, momentum, weights and biases.

_did_split - Variable in class hex.tree.SharedTree.ScoreBuildOneTree

_dinfo - Variable in class hex.FrameTask

_dinfo - Variable in class hex.FrameTask2

_dinfo - Variable in class hex.gam.GAMModel.GAMModelOutput

_dinfo - Variable in class hex.gram.Gram.OuterGramTask

_dinfo - Variable in class hex.hglm.HGLMModel.HGLMModelOutput

_direction - Variable in class hex.optimization.OptimizationUtils.ExactLineSearch

_disable_algo_check - Variable in class hex.generic.GenericModelParameters

Skip the check for white-listed algorithms, this allows load any MOJO.

_disable_training_metrics - Variable in class hex.psvm.PSVMModel.PSVMParameters

_disable_training_metrics - Variable in class hex.tree.isoforextended.ExtendedIsolationForestModel.ExtendedIsolationForestParameters

Disable calculating training metrics (expensive on large datasets).

_dispersion_epsilon - Variable in class hex.glm.GLMModel.GLMParameters

_dispersion_estimated - Variable in class hex.glm.GLMModel.GLMParameters

_dispersion_learning_rate - Variable in class hex.glm.GLMModel.GLMParameters

_dispersion_parameter_method - Variable in class hex.glm.GLMModel.GLMParameters

_dist - Variable in class hex.tree.Constraints

_domains - Variable in class hex.tree.CompressedForest

_domains - Variable in class hex.tree.CompressedForest.LocalCompressedForest

_dropout - Variable in class hex.deeplearning.Neurons

For Dropout training

_e - Variable in class hex.deeplearning.Neurons

_early_stopping - Variable in class hex.gam.GAMModel.GAMParameters

_early_stopping - Variable in class hex.glm.GLMModel.GLMParameters

_eigenvectors - Variable in class hex.glrm.GLRMModel.GLRMOutput

_eigenvectors - Variable in class hex.pca.PCAModel.PCAOutput

_eigenvectors_raw - Variable in class hex.glrm.GLRMModel.GLRMOutput

_eigenvectors_raw - Variable in class hex.pca.PCAModel.PCAOutput

_elastic_averaging - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

_elastic_averaging_moving_rate - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

_elastic_averaging_regularization - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

_em_epsilon - Variable in class hex.hglm.HGLMModel.HGLMParameters

_encoding - Variable in class hex.tree.SharedTreePojoWriter

_epochs - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

The number of passes over the training dataset to be carried out.

_epochs - Variable in class hex.word2vec.Word2VecModel.Word2VecOutput

_epochs - Variable in class hex.word2vec.Word2VecModel.Word2VecParameters

_EPS - Static variable in class hex.glm.GLMModel

_eps_prob - Variable in class hex.naivebayes.NaiveBayesModel.NaiveBayesParameters

_eps_sdev - Variable in class hex.naivebayes.NaiveBayesModel.NaiveBayesParameters

_epsilon - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

The second of two hyper parameters for adaptive learning rate (ADADELTA).

_epsilonkCSSquare - Variable in class hex.glm.ConstrainedGLMUtils.ConstraintGLMStates

_equalityConstraintsBeta - Variable in class hex.glm.GLMModel.GLMOutput

_equalityConstraintsLinear - Variable in class hex.glm.GLMModel.GLMOutput

_estimate_k - Variable in class hex.kmeans.KMeansModel.KMeansParameters

_exemplar_assignment_vec_key - Variable in class hex.aggregator.AggregatorModel

_exemplars - Variable in class hex.aggregator.AggregatorModel

_exp_coef - Variable in class hex.coxph.CoxPHModel.CoxPHOutput

_exp_neg_coef - Variable in class hex.coxph.CoxPHModel.CoxPHOutput

_expand - Variable in class hex.tree.SharedTreeModelWithContributions.ScoreContributionsWithBackgroundTask

_expand_user_y - Variable in class hex.glrm.GLRMModel.GLRMParameters

_explained_deviance_train - Variable in class hex.glm.GLMModel.RegularizationPath

_explained_deviance_valid - Variable in class hex.glm.GLMModel.RegularizationPath

_export_weights_and_biases - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

_expose_constraints - Variable in class hex.glm.GLMModel.GLMParameters

_extension_level - Variable in class hex.tree.isoforextended.ExtendedIsolationForestModel.ExtendedIsolationForestParameters

Maximum is N - 1 (N = numCols).

_fact_threshold - Variable in class hex.psvm.PSVMModel.PSVMParameters

_family - Variable in class hex.anovaglm.ANOVAGLMModel.ANOVAGLMParameters

_family - Variable in class hex.gam.GAMModel.GAMParameters

_family - Variable in class hex.glm.GLMModel.GLMParameters

_family - Variable in class hex.glm.GLMModel.GLMWeightsFun

_family - Variable in class hex.hglm.HGLMModel.HGLMParameters

_fast_mode - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

Enable fast mode (minor approximation in back-propagation), should not affect results significantly.

_feasible_threshold - Variable in class hex.psvm.psvm.PrimalDualIPM.Parms

_feasible_threshold - Variable in class hex.psvm.PSVMModel.PSVMParameters

_featureIndex - Variable in class hex.tree.dt.AbstractSplittingRule

_features - Variable in class hex.tree.TreeHandler.TreeProperties

_featureSplit - Variable in class hex.tree.dt.mrtasks.CountBinsSamplesCountsMRTask

_finalScoring - Variable in class hex.glm.GLMModel

_first_diag - Variable in class hex.gam.MatrixFrameUtils.TriDiagonalMatrix

_fix_dispersion_parameter - Variable in class hex.glm.GLMModel.GLMParameters

_fix_tweedie_variance_power - Variable in class hex.glm.GLMModel.GLMParameters

_fixed_coefficient_names - Variable in class hex.hglm.HGLMModel.HGLMModelOutput

_fold - Variable in class hex.DataInfo

_force_load_balance - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

Increase training speed on small datasets by splitting it into many chunks to allow utilization of all cores.

_forest - Variable in class hex.tree.DTreeScorer

_frame2DProduce - Variable in class hex.gram.Gram

_fullInfo - Variable in class hex.glm.ComputationState.GLMSubsetGinfo

_gam_columns - Variable in class hex.gam.GAMModel.GAMParameters

_gam_columns_sorted - Variable in class hex.gam.GAMModel.GAMParameters

_gam_knot_column_names - Variable in class hex.gam.GAMModel.GAMModelOutput

_gam_transformed_center_key - Variable in class hex.gam.GAMModel.GAMModelOutput

_gamColIndices - Variable in class hex.glm.GLM

_gamColMeans - Variable in class hex.gam.GAMModel

_gamColMeansRaw - Variable in class hex.gam.GAMModel.GAMModelOutput

_gamColNames - Variable in class hex.gam.GAMModel

_gamColNames - Variable in class hex.gam.GAMModel.GAMModelOutput

_gamColnames - Variable in class hex.glm.GLM

_gamColNamesNoCentering - Variable in class hex.gam.GAMModel

_gamCols2Add - Variable in class hex.gam.MatrixFrameUtils.AddCSGamColumns

_gamCols2Add - Variable in class hex.gam.MatrixFrameUtils.AddTPKnotsGamColumns

_gamFrameKeysCenter - Variable in class hex.gam.GAMModel

_gamFrameKeysCenter - Variable in class hex.gam.MatrixFrameUtils.AddTPKnotsGamColumns

_gamma - Variable in class hex.psvm.PSVMModel.PSVMParameters

_gamma_x - Variable in class hex.glrm.GLRMModel.GLRMParameters

_gamma_y - Variable in class hex.glrm.GLRMModel.GLRMParameters

_gamPredSize - Variable in class hex.gam.GAMModel

_gamPredSize - Variable in class hex.gam.GAMModel.GAMParameters

_gamTransformedTrainCenter - Variable in class hex.gam.GAMModel.GAMModelOutput

_gen_syn_data - Variable in class hex.hglm.HGLMModel.HGLMParameters

_generate_scoring_history - Variable in class hex.gam.GAMModel.GAMParameters

_generate_scoring_history - Variable in class hex.glm.GLMModel.GLMParameters

_generate_variable_inflation_factors - Variable in class hex.glm.GLMModel.GLMParameters

_generatedWeights - Variable in class hex.glm.GLM

_ginfoOriginal - Variable in class hex.optimization.OptimizationUtils.ExactLineSearch

_glm_best_lamda_value - Variable in class hex.gam.GAMModel.GAMModelOutput

_glm_cv_scoring_history - Variable in class hex.gam.GAMModel.GAMModelOutput

_glm_dispersion - Variable in class hex.gam.GAMModel.GAMModelOutput

_glm_model_summary - Variable in class hex.gam.GAMModel.GAMModelOutput

_glm_pvalues - Variable in class hex.gam.GAMModel.GAMModelOutput

_glm_scoring_history - Variable in class hex.gam.GAMModel.GAMModelOutput

_glm_stdErr - Variable in class hex.gam.GAMModel.GAMModelOutput

_glm_training_metrics - Variable in class hex.gam.GAMModel.GAMModelOutput

_glm_validation_metrics - Variable in class hex.gam.GAMModel.GAMModelOutput

_glm_vcov - Variable in class hex.gam.GAMModel.GAMModelOutput

_glm_zvalues - Variable in class hex.gam.GAMModel.GAMModelOutput

_glmNFolds - Variable in class hex.gam.GAM

_glmNFolds - Variable in class hex.modelselection.ModelSelection

_glmType - Variable in class hex.glm.GLMModel.GLMParameters

_globalSplitPointsKey - Variable in class hex.tree.DHistogram

_grad - Variable in class hex.glm.ComputationState.GramGrad

_gradient - Variable in class hex.glm.GLMTask.GLMMultinomialGradientBaseTask

_gradient - Variable in class hex.optimization.OptimizationUtils.GradientInfo

_gradient_epsilon - Variable in class hex.gam.GAMModel.GAMParameters

_gradient_epsilon - Variable in class hex.glm.GLMModel.GLMParameters

_gradient_epsilon - Variable in class hex.modelselection.ModelSelectionModel.ModelSelectionParameters

_gram - Variable in class hex.glm.ComputationState.GramGrad

_gram - Variable in class hex.glm.GLMTask.GLMIterationTask

_gram - Variable in class hex.glm.GLMTask.LSTask

_gram - Variable in class hex.gram.Gram.GramTask

_gram - Variable in class hex.gram.Gram.OuterGramTask

_group_column - Variable in class hex.hglm.HGLMModel.HGLMParameters

_group_column_names - Variable in class hex.hglm.HGLMModel.HGLMModelOutput

_hasMetalearnerParams - Variable in class hex.ensemble.Metalearner

_hidden - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

The number and size of each hidden layer in the model.

_hidden_dropout_ratios - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

A fraction of the inputs for each hidden layer to be omitted from training in order to improve generalization.

_highest_interaction_term - Variable in class hex.anovaglm.ANOVAGLMModel.ANOVAGLMParameters

_histo_monitor_class - Variable in class hex.tree.SharedTree.SharedTreeDebugParams

_histogram_type - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters

_history_average_SEE - Variable in class hex.svd.SVDModel.SVDOutput

_history_eigenVectorIndex - Variable in class hex.svd.SVDModel.SVDOutput

_history_err - Variable in class hex.svd.SVDModel.SVDOutput

_history_objective - Variable in class hex.glrm.GLRMModel.GLRMOutput

_history_step_size - Variable in class hex.glrm.GLRMModel.GLRMOutput

_history_withinss - Variable in class hex.kmeans.KMeansModel.KMeansOutput

_histoType - Variable in class hex.tree.DHistogram

_hj - Variable in class hex.gam.GamSplines.CubicRegressionSplines

_hs - Variable in class hex.tree.DTree.UndecidedNode

_hyper_param - Variable in class hex.psvm.PSVMModel.PSVMParameters

_icc - Variable in class hex.hglm.HGLMModel.HGLMModelOutput

_ics - Variable in class hex.tree.SharedTree

_importance - Variable in class hex.glrm.GLRMModel.GLRMOutput

_importance - Variable in class hex.pca.PCAModel.PCAOutput

_improvPerVar - Variable in class hex.tree.SharedTree

_impute_missing - Variable in class hex.pca.PCAModel.PCAParameters

_impute_missing - Variable in class hex.svd.SVDModel.SVDParameters

_impute_original - Variable in class hex.glrm.GLRMModel.GLRMParameters

_impute_original - Variable in class hex.glrm.ModelMetricsGLRM.GlrmModelMetricsBuilder

_imputeMissing - Variable in class hex.anovaglm.GenerateTransformColumns

_imputeMissing - Variable in class hex.DataInfo

_in_training_checkpoints_dir - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters

_in_training_checkpoints_tree_interval - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters

_index - Variable in class hex.deeplearning.Neurons

_influence - Variable in class hex.glm.GLMModel.GLMParameters

_influence - Variable in class hex.modelselection.ModelSelectionModel.ModelSelectionParameters

_init - Variable in class hex.coxph.CoxPHModel.CoxPHParameters

_init - Variable in class hex.glrm.GLRMModel.GLRMParameters

_init - Variable in class hex.kmeans.KMeansModel.KMeansParameters

_init_dispersion_parameter - Variable in class hex.glm.GLMModel.GLMParameters

_init_f - Variable in class hex.tree.SharedTreeModel.SharedTreeOutput

InitF value (for zero trees) f0 = mean(yi) for gaussian f0 = log(yi/1-yi) for bernoulli For GBM bernoulli, the initial prediction for 0 trees is p = 1/(1+exp(-f0)) From this, the mse for 0 trees (null model) can be computed as follows: mean((yi-p)^2)

_init_key - Variable in class hex.glrm.GLRMModel.GLRMOutput

_init_learning_rate - Variable in class hex.word2vec.Word2VecModel.Word2VecParameters

_init_optimal_glm - Variable in class hex.glm.GLMModel.GLMParameters

_init_step_size - Variable in class hex.glrm.GLRMModel.GLRMParameters

_initChunks - Variable in class hex.gam.GamSplines.ThinPlateRegressionUtils.ScaleTPPenalty

_initChunks - Variable in class hex.gam.MatrixFrameUtils.GenCSSplineGamOneColumn

_initConstraintMatrix - Variable in class hex.glm.GLMModel.GLMOutput

_initial_biases - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

Frame keys for initial bias vectors

_initial_fixed_effects - Variable in class hex.hglm.HGLMModel.HGLMParameters

_initial_random_effects - Variable in class hex.hglm.HGLMModel.HGLMParameters

_initial_score_interval - Variable in class hex.tree.isoforextended.ExtendedIsolationForestModel.ExtendedIsolationForestParameters

For _initial_score_interval milliseconds - score each iteration of the algorithm.

_initial_score_interval - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters

_initial_t_matrix - Variable in class hex.hglm.HGLMModel.HGLMParameters

_initial_weight_distribution - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

The distribution from which initial weights are to be drawn.

_initial_weight_scale - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

The scale of the distribution function for Uniform or Normal distributions.

_initial_weights - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

Frame keys for initial weight matrices

_initialPrediction - Variable in class hex.tree.SharedTree

_initNA - Variable in class hex.tree.DHistogram

_input - Variable in class hex.deeplearning.Neurons

_input_dropout_ratio - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

A fraction of the features for each training row to be omitted from training in order to improve generalization (dimension sampling).

_interaction_constraints - Variable in class hex.tree.gbm.GBMModel.GBMParameters

_interaction_pairs - Variable in class hex.coxph.CoxPHModel.CoxPHParameters

_interaction_pairs - Variable in class hex.gam.GAMModel.GAMParameters

_interaction_pairs - Variable in class hex.glm.GLMModel.GLMParameters

_interactions - Variable in class hex.anovaglm.ANOVAGLMModel.ANOVAGLMParameters

_interactions - Variable in class hex.coxph.CoxPHModel.CoxPHParameters

_interactions - Variable in class hex.DataInfo

_interactions - Variable in class hex.gam.GAMModel.GAMParameters

_interactions - Variable in class hex.glm.GLMModel.GLMParameters

_interactions - Variable in class hex.modelselection.ModelSelectionModel.ModelSelectionParameters

_interactions_only - Variable in class hex.coxph.CoxPHModel.CoxPHParameters

_interactionSpec - Variable in class hex.DataInfo

_interactionVecs - Variable in class hex.DataInfo

_intercept - Variable in class hex.DataInfo

_intercept - Variable in class hex.gam.GAMModel.GAMParameters

_intercept - Variable in class hex.glm.GLMModel.GLMParameters

_intercept - Variable in class hex.modelselection.ModelSelectionModel.ModelSelectionParameters

_intercept - Variable in class hex.rulefit.RuleFitModel.RuleFitOutput

_intLvls - Variable in class hex.DataInfo

_intOpt - Variable in class hex.tree.DHistogram

_invTheta - Variable in class hex.anovaglm.ANOVAGLMModel.ANOVAGLMParameters

_invTheta - Variable in class hex.glm.GLMModel.GLMParameters

_isInt - Variable in class hex.tree.DHistogram

_iSplineNum - Variable in class hex.gam.GAMModel

_iterations - Variable in class hex.glrm.GLRMModel.GLRMOutput

_iterations - Variable in class hex.hglm.HGLMModel.HGLMModelOutput

_iterations - Variable in class hex.kmeans.KMeansModel.KMeansOutput

_iterations - Variable in class hex.svd.SVDModel.SVDOutput

_iTreeKeys - Variable in class hex.tree.isoforextended.ExtendedIsolationForestModel.ExtendedIsolationForestOutput

_job - Variable in class hex.ensemble.Metalearner

_jobKey - Variable in class hex.FrameTask

_k - Variable in class hex.aggregator.AggregatorModel.AggregatorParameters

_k - Variable in class hex.glrm.GLRMModel.GLRMParameters

_k - Variable in class hex.kmeans.KMeansModel.KMeansOutput

_k - Variable in class hex.pca.PCAModel.PCAParameters

_keep_base_model_predictions - Variable in class hex.ensemble.StackedEnsembleModel.StackedEnsembleParameters

_keep_gam_cols - Variable in class hex.gam.GAMModel.GAMParameters

_keep_levelone_frame - Variable in class hex.ensemble.StackedEnsembleModel.StackedEnsembleParameters

_keep_orig_histo_precision - Variable in class hex.tree.SharedTree.SharedTreeDebugParams

_keep_u - Variable in class hex.svd.SVDModel.SVDParameters

_keepBetaDiffVar - Variable in class hex.glm.GLMModel.GLMParameters

_kernel_type - Variable in class hex.psvm.PSVMModel.PSVMParameters

_knot_ids - Variable in class hex.gam.GAMModel.GAMParameters

_knot_locations - Variable in class hex.gam.GAMModel.GAMModelOutput

_knots - Variable in class hex.gam.GAMModel.GAMModelOutput

_knots - Variable in class hex.gam.GamSplines.CubicRegressionSplines

_knots - Variable in class hex.gam.MatrixFrameUtils.GenCSSplineGamOneColumn

_l1 - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

A regularization method that constrains the absolute value of the weights and has the net effect of dropping some weights (setting them to zero) from a model to reduce complexity and avoid overfitting.

_l2 - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

A regularization method that constrains the sum of the squared weights.

_lambda - Variable in class hex.anovaglm.ANOVAGLMModel.ANOVAGLMParameters

_lambda - Variable in class hex.gam.GAMModel.GAMParameters

_lambda - Variable in class hex.glm.GLMModel.GLMParameters

_lambda - Variable in class hex.modelselection.ModelSelectionModel.ModelSelectionParameters

_lambda - Variable in class hex.rulefit.RuleFitModel.RuleFitParameters

_lambda_1se - Variable in class hex.glm.GLMModel.GLMOutput

_lambda_max - Variable in class hex.glm.GLMModel

_lambda_max - Variable in class hex.glm.GLMModel.GLMOutput

_lambda_min - Variable in class hex.glm.GLMModel.GLMOutput

_lambda_min_ratio - Variable in class hex.gam.GAMModel.GAMParameters

_lambda_min_ratio - Variable in class hex.glm.GLMModel.GLMParameters

_lambda_search - Variable in class hex.anovaglm.ANOVAGLMModel.ANOVAGLMParameters

_lambda_search - Variable in class hex.gam.GAMModel.GAMParameters

_lambda_search - Variable in class hex.glm.GLMModel.GLMParameters

_lambda_search - Variable in class hex.modelselection.ModelSelectionModel.ModelSelectionParameters

_lambdaLS - Variable in class hex.optimization.OptimizationUtils.ExactLineSearch

_lambdas - Variable in class hex.glm.GLMModel.RegularizationPath

_laplace - Variable in class hex.naivebayes.NaiveBayesModel.NaiveBayesParameters

_lastScoredTree - Variable in class hex.tree.SharedTree

_leafNodeAssignments - Variable in class hex.tree.TreeHandler.TreeProperties

_learn_rate - Variable in class hex.adaboost.AdaBoostModel.AdaBoostParameters

Specify how quickly the training converge.

_learn_rate - Variable in class hex.tree.gbm.GBMModel.GBMParameters

_learn_rate_annealing - Variable in class hex.tree.gbm.GBMModel.GBMParameters

_leaves - Variable in class hex.tree.DTree

_leftChildren - Variable in class hex.tree.TreeHandler.TreeProperties

_leftCount - Variable in class hex.tree.dt.binning.SplitStatistics

_leftCount0 - Variable in class hex.tree.dt.binning.SplitStatistics

_len - Variable in class hex.tree.DTree

_lessThanEqualToConstraintsBeta - Variable in class hex.glm.GLMModel.GLMOutput

_lessThanEqualToConstraintsLinear - Variable in class hex.glm.GLMModel.GLMOutput

_levelone_frame_id - Variable in class hex.ensemble.StackedEnsembleModel.StackedEnsembleOutput

_levelOneTrainingFrame - Variable in class hex.ensemble.Metalearner

_levelOneValidationFrame - Variable in class hex.ensemble.Metalearner

_levels - Variable in class hex.naivebayes.NaiveBayesModel.NaiveBayesOutput

_likelihood - Variable in class hex.glm.GLMTask.GLMIterationTask

_limitNumSamplesForSplit - Variable in class hex.tree.dt.DTModel.DTOutput

_linear_constraint_states - Variable in class hex.glm.GLMModel.GLMOutput

_linear_constraints - Variable in class hex.glm.GLMModel.GLMParameters

_linear_constraints_table - Variable in class hex.glm.GLMModel.GLMOutput

_link - Variable in class hex.anovaglm.ANOVAGLMModel.ANOVAGLMParameters

_link - Variable in class hex.gam.GAMModel.GAMParameters

_link - Variable in class hex.glm.GLMModel.GLMParameters

_link - Variable in class hex.modelselection.ModelSelectionModel.ModelSelectionParameters

_loading_name - Variable in class hex.glrm.GLRMModel.GLRMParameters

Deprecated.

_log_likelihood - Variable in class hex.hglm.HGLMModel.HGLMModelOutput

_log_likelihood_valid - Variable in class hex.hglm.HGLMModel.HGLMModelOutput

_loss - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

The loss (error) function to be minimized by the model.

_loss - Variable in class hex.glrm.GLRMModel.GLRMParameters

_loss_by_col - Variable in class hex.glrm.GLRMModel.GLRMParameters

_loss_by_col_idx - Variable in class hex.glrm.GLRMModel.GLRMParameters

_lossFunc - Variable in class hex.glrm.GLRMModel.GLRMOutput

_lre_min - Variable in class hex.coxph.CoxPHModel.CoxPHParameters

_lsNeeded - Variable in class hex.glm.ComputationState

_m - Variable in class hex.gam.GAMModel

_M - Variable in class hex.gam.GAMModel

_m - Variable in class hex.gam.GAMModel.GAMParameters

_M - Variable in class hex.gam.GAMModel.GAMParameters

_mapping_frame - Variable in class hex.aggregator.AggregatorModel.AggregatorOutput

_mask - Variable in class hex.tree.dt.CategoricalFeatureLimits

_matches - Variable in class hex.grep.GrepModel.GrepOutput

_max - Variable in class hex.tree.dt.binning.NumericBin

_max - Variable in class hex.tree.dt.NumericFeatureLimits

_max_abs_leafnode_pred - Variable in class hex.tree.gbm.GBMModel.GBMParameters

_max_active_predictors - Variable in class hex.gam.GAMModel.GAMParameters

_max_active_predictors - Variable in class hex.glm.GLMModel.GLMParameters

_max_categorical_features - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

Max.

_max_depth - Variable in class hex.tree.dt.DTModel.DTOutput

_max_depth - Variable in class hex.tree.dt.DTModel.DTParameters

Depth (max depth) of the tree

_max_depth - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters

_max_depth - Variable in class hex.tree.TreeStats

_max_iter - Variable in class hex.psvm.psvm.PrimalDualIPM.Parms

_max_iterations - Variable in class hex.coxph.CoxPHModel.CoxPHParameters

_max_iterations - Variable in class hex.gam.GAMModel.GAMParameters

_max_iterations - Variable in class hex.glm.GLMModel.GLMParameters

_max_iterations - Variable in class hex.glrm.GLRMModel.GLRMParameters

_max_iterations - Variable in class hex.hglm.HGLMModel.HGLMParameters

_max_iterations - Variable in class hex.kmeans.KMeansModel.KMeansParameters

_max_iterations - Variable in class hex.pca.PCAModel.PCAParameters

_max_iterations - Variable in class hex.psvm.PSVMModel.PSVMParameters

_max_iterations - Variable in class hex.svd.SVDModel.SVDParameters

_max_iterations_dispersion - Variable in class hex.glm.GLMModel.GLMParameters

_max_leaves - Variable in class hex.tree.TreeStats

_max_num_rules - Variable in class hex.rulefit.RuleFitModel.RuleFitParameters

_max_path_length - Variable in class hex.tree.isofor.IsolationForestModel.IsolationForestOutput

_max_predictor_number - Variable in class hex.modelselection.ModelSelectionModel.ModelSelectionParameters

_max_rule_length - Variable in class hex.rulefit.RuleFitModel.RuleFitParameters

_max_series_index - Variable in class hex.glm.GLMModel.GLMParameters

_max_updates - Variable in class hex.glrm.GLRMModel.GLRMParameters

_max_w2 - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

A maximum on the sum of the squared incoming weights into any one neuron.

_max_x - Variable in class hex.isotonic.IsotonicRegressionModel.IsotonicRegressionOutput

_maxDepth - Variable in class hex.tree.isoforextended.isolationtree.IsolationTreeStats

_maxEx - Variable in class hex.tree.DHistogram

_maxIn - Variable in class hex.tree.DHistogram

_maxIndex - Variable in class hex.util.LinearAlgebraUtils.FindMaxIndex

_maxIsolated - Variable in class hex.tree.isoforextended.isolationtree.IsolationTreeStats

_maxIteration - Variable in class hex.optimization.OptimizationUtils.ExactLineSearch

_maxLeaves - Variable in class hex.tree.isoforextended.isolationtree.IsolationTreeStats

_maxNotIsolated - Variable in class hex.tree.isoforextended.isolationtree.IsolationTreeStats

_maxRuntimeSecs - Variable in class hex.ensemble.Metalearner

_maxZeroSplits - Variable in class hex.tree.isoforextended.isolationtree.IsolationTreeStats

_mean_depth - Variable in class hex.tree.TreeStats

_mean_leaves - Variable in class hex.tree.TreeStats

_mean_normalized_score - Variable in class hex.tree.isofor.ModelMetricsAnomaly

Mean normalized score should be (but not necessary is) a number between 0 and 1.

_mean_score - Variable in class hex.tree.isofor.ModelMetricsAnomaly

The raw number that an algorithm is using to count final anomaly score.

_meanDepth - Variable in class hex.tree.isoforextended.isolationtree.IsolationTreeStats

_meanIsolated - Variable in class hex.tree.isoforextended.isolationtree.IsolationTreeStats

_meanLeaves - Variable in class hex.tree.isoforextended.isolationtree.IsolationTreeStats

_meanNotIsolated - Variable in class hex.tree.isoforextended.isolationtree.IsolationTreeStats

_meanZeroSplits - Variable in class hex.tree.isoforextended.isolationtree.IsolationTreeStats

_metalearner - Variable in class hex.ensemble.StackedEnsembleModel.StackedEnsembleOutput

_metalearner_algorithm - Variable in class hex.ensemble.StackedEnsembleModel.StackedEnsembleParameters

_metalearner_fold_assignment - Variable in class hex.ensemble.StackedEnsembleModel.StackedEnsembleParameters

_metalearner_fold_column - Variable in class hex.ensemble.StackedEnsembleModel.StackedEnsembleParameters

_metalearner_nfolds - Variable in class hex.ensemble.StackedEnsembleModel.StackedEnsembleParameters

_metalearner_parameters - Variable in class hex.ensemble.Metalearner

_metalearner_parameters - Variable in class hex.ensemble.StackedEnsembleModel.StackedEnsembleParameters

_metalearner_params - Variable in class hex.ensemble.StackedEnsembleModel.StackedEnsembleParameters

_metalearner_transform - Variable in class hex.ensemble.StackedEnsembleModel.StackedEnsembleParameters

_metalearnerJob - Variable in class hex.ensemble.Metalearner

_metalearnerKey - Variable in class hex.ensemble.Metalearner

_metalearnerSeed - Variable in class hex.ensemble.Metalearner

_method - Variable in class hex.glm.TweedieEstimator

_method - Variable in class hex.hglm.HGLMModel.HGLMParameters

_min - Variable in class hex.tree.DHistogram

_min - Variable in class hex.tree.dt.binning.NumericBin

_min - Variable in class hex.tree.dt.NumericFeatureLimits

_min2 - Variable in class hex.tree.DHistogram

_min_depth - Variable in class hex.tree.TreeStats

_min_leaves - Variable in class hex.tree.TreeStats

_min_path_length - Variable in class hex.tree.isofor.IsolationForestModel.IsolationForestOutput

_min_predictor_number - Variable in class hex.modelselection.ModelSelectionModel.ModelSelectionParameters

_min_prob - Variable in class hex.naivebayes.NaiveBayesModel.NaiveBayesParameters

_min_rows - Variable in class hex.tree.dt.DTModel.DTParameters

_min_rows - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters

_min_rule_length - Variable in class hex.rulefit.RuleFitModel.RuleFitParameters

_min_sdev - Variable in class hex.naivebayes.NaiveBayesModel.NaiveBayesParameters

_min_split_improvement - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters

_min_step_size - Variable in class hex.glrm.GLRMModel.GLRMParameters

_min_word_freq - Variable in class hex.word2vec.Word2VecModel.Word2VecParameters

_min_x - Variable in class hex.isotonic.IsotonicRegressionModel.IsotonicRegressionOutput

_minDepth - Variable in class hex.tree.isoforextended.isolationtree.IsolationTreeStats

_mini_batch_size - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

_minInt - Variable in class hex.tree.DHistogram

_minIsolated - Variable in class hex.tree.isoforextended.isolationtree.IsolationTreeStats

_minLeaves - Variable in class hex.tree.isoforextended.isolationtree.IsolationTreeStats

_minNotIsolated - Variable in class hex.tree.isoforextended.isolationtree.IsolationTreeStats

_minSplitImprovement - Variable in class hex.tree.DHistogram

_minZeroSplits - Variable in class hex.tree.isoforextended.isolationtree.IsolationTreeStats

_miscls - Variable in class hex.glrm.ModelMetricsGLRM.GlrmModelMetricsBuilder

_missing_values_handling - Variable in class hex.anovaglm.ANOVAGLMModel.ANOVAGLMParameters

_missing_values_handling - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

_missing_values_handling - Variable in class hex.gam.GAMModel.GAMParameters

_missing_values_handling - Variable in class hex.glm.GLMModel.GLMParameters

_missing_values_handling - Variable in class hex.hglm.HGLMModel.HGLMParameters

_missing_values_handling - Variable in class hex.modelselection.ModelSelectionModel.ModelSelectionParameters

_mode - Variable in class hex.modelselection.ModelSelectionModel.ModelSelectionModelOutput

_mode - Variable in class hex.modelselection.ModelSelectionModel.ModelSelectionParameters

_model - Variable in class hex.ensemble.Metalearner

_model - Variable in class hex.ensemble.StackedEnsemble

_model - Variable in class hex.tree.SharedTree

_model - Variable in class hex.tree.SharedTreeModelWithContributions.ScoreContributionsTask

_model - Variable in class hex.tree.SharedTreeModelWithContributions.ScoreContributionsWithBackgroundTask

_model_beta - Variable in class hex.gam.GAMModel.GAMModelOutput

_model_beta_multinomial - Variable in class hex.gam.GAMModel.GAMModelOutput

_model_beta_multinomial_no_centering - Variable in class hex.gam.GAMModel.GAMModelOutput

_model_beta_no_centering - Variable in class hex.gam.GAMModel.GAMModelOutput

_model_key - Variable in class hex.generic.GenericModelParameters

Key to the file with embedded model

_model_type - Variable in class hex.rulefit.RuleFitModel.RuleFitParameters

_modelCategory - Variable in class hex.generic.GenericModelOutput

_modelKey - Variable in class hex.tree.SharedTreeModelWithContributions.ScoreContributionsTask

_modelKey - Variable in class hex.tree.SharedTreeModelWithContributions.ScoreContributionsWithBackgroundTask

_modelKey - Variable in class hex.tree.SharedTreePojoWriter

_modelParameters - Variable in class hex.generic.GenericModelParameters

Generic model parameters - might contain any parameters based on the state of the model in the training phase.

_momentum_ramp - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

The momentum_ramp parameter controls the amount of learning for which momentum increases (assuming momentum_stable is larger than momentum_start).

_momentum_stable - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

The momentum_stable parameter controls the final momentum value reached after momentum_ramp training samples.

_momentum_start - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

The momentum_start parameter controls the amount of momentum at the beginning of training.

_monotone_constraints - Variable in class hex.tree.gbm.GBMModel.GBMParameters

_mSplineNum - Variable in class hex.gam.GAMModel

_mtries - Variable in class hex.tree.drf.DRFModel.DRFParameters

_mtries - Variable in class hex.tree.isofor.IsolationForestModel.IsolationForestParameters

_mtries - Variable in class hex.tree.uplift.UpliftDRFModel.UpliftDRFParameters

_mtry - Variable in class hex.tree.SharedTree

_mtry_per_tree - Variable in class hex.tree.SharedTree

_mtrys - Variable in class hex.tree.DTree

_mtrys_per_tree - Variable in class hex.tree.DTree

_mu_factor - Variable in class hex.psvm.psvm.PrimalDualIPM.Parms

_mu_factor - Variable in class hex.psvm.PSVMModel.PSVMParameters

_multi_loss - Variable in class hex.glrm.GLRMModel.GLRMParameters

_multinode_mode - Variable in class hex.modelselection.ModelSelectionModel.ModelSelectionParameters

_multinomial - Variable in class hex.glm.GLMModel.GLMOutput

_name - Variable in class hex.tree.DHistogram

_names_expanded - Variable in class hex.glrm.GLRMModel.GLRMOutput

_names_expanded - Variable in class hex.svd.SVDModel.SVDOutput

_nas - Variable in class hex.tree.TreeHandler.TreeProperties

_nBetas - Variable in class hex.glm.GLM.BetaInfo

_nbin - Variable in class hex.tree.DHistogram

_nbins - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters

_nbins_cats - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters

_nbins_top_level - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters

_ncats - Variable in class hex.glrm.GLRMModel.GLRMOutput

_ncats - Variable in class hex.naivebayes.NaiveBayesModel.NaiveBayesOutput

_ncats - Variable in class hex.pca.PCAModel.PCAOutput

_ncats - Variable in class hex.svd.SVDModel.SVDOutput

_nclass - Variable in class hex.gam.GAMModel

_nclass - Variable in class hex.tree.DTreeScorer

_ncols - Variable in class hex.tree.DTreeScorer

_ncols - Variable in class hex.tree.SharedTree

_negative_weight - Variable in class hex.psvm.PSVMModel.PSVMParameters

_nesterov_accelerated_gradient - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

The Nesterov accelerated gradient descent method is a modification to traditional gradient descent for convex functions.

_newBeta - Variable in class hex.optimization.OptimizationUtils.ExactLineSearch

_newColNumber - Variable in class hex.anovaglm.GenerateTransformColumns

_nfeatures - Variable in class hex.generic.GenericModelOutput

_nfolds - Variable in class hex.anovaglm.ANOVAGLMModel.ANOVAGLMParameters

_nfolds - Variable in class hex.modelselection.ModelSelectionModel.ModelSelectionParameters

_nid - Variable in class hex.tree.DTree.Node

_nids - Variable in class hex.tree.DTree.DecidedNode

_nlambdas - Variable in class hex.gam.GAMModel.GAMParameters

_nlambdas - Variable in class hex.glm.GLMModel.GLMParameters

_nlearners - Variable in class hex.adaboost.AdaBoostModel.AdaBoostParameters

Number of weak learners to train.

_nnums - Variable in class hex.glrm.GLRMModel.GLRMOutput

_nnums - Variable in class hex.pca.PCAModel.PCAOutput

_nnums - Variable in class hex.svd.SVDModel.SVDOutput

_nobs - Variable in class hex.gam.GAMModel

_nobs - Variable in class hex.glm.GLMModel

_nobs - Variable in class hex.glrm.GLRMModel.GLRMOutput

_nobs - Variable in class hex.gram.Gram.GramTask

_nobs - Variable in class hex.gram.Gram.OuterGramTask

_nobs - Variable in class hex.hglm.HGLMModel.HGLMModelOutput

_nobs - Variable in class hex.hglm.MetricBuilderHGLM

_nobs - Variable in class hex.isotonic.IsotonicRegressionModel.IsotonicRegressionOutput

_nobs - Variable in class hex.pca.PCAModel.PCAOutput

_nobs - Variable in class hex.svd.SVDModel.SVDOutput

_nobs_valid - Variable in class hex.hglm.HGLMModel.HGLMModelOutput

_nodes - Variable in class hex.tree.TreeVisitor

_non_negative - Variable in class hex.gam.GAMModel.GAMParameters

_non_negative - Variable in class hex.glm.GLMModel.GLMParameters

_noReg - Variable in class hex.glm.ComputationState

_norm_model - Variable in class hex.word2vec.Word2VecModel.Word2VecParameters

_normMul - Variable in class hex.DataInfo

_normMul - Variable in class hex.glrm.GLRMModel.GLRMOutput

_normMul - Variable in class hex.pca.PCAModel.PCAOutput

_normMul - Variable in class hex.svd.SVDModel.SVDOutput

_normMulnew - Variable in class hex.glm.GLMTask.GLMCoordinateDescentTaskSeqNaive

_normMulold - Variable in class hex.glm.GLMTask.GLMCoordinateDescentTaskSeqNaive

_normRespMul - Variable in class hex.DataInfo

_normRespSub - Variable in class hex.DataInfo

_normSigmaStandardizationOff - Variable in class hex.DataInfo

_normSub - Variable in class hex.DataInfo

_normSub - Variable in class hex.glrm.GLRMModel.GLRMOutput

_normSub - Variable in class hex.pca.PCAModel.PCAOutput

_normSub - Variable in class hex.svd.SVDModel.SVDOutput

_normSubnew - Variable in class hex.glm.GLMTask.GLMCoordinateDescentTaskSeqNaive

_normSubold - Variable in class hex.glm.GLMTask.GLMCoordinateDescentTaskSeqNaive

_normSubStandardizationOff - Variable in class hex.DataInfo

_nparallelism - Variable in class hex.anovaglm.ANOVAGLMModel.ANOVAGLMParameters

_nparallelism - Variable in class hex.modelselection.ModelSelectionModel.ModelSelectionParameters

_nrows - Variable in class hex.DataInfo.Rows

_nrows - Variable in class hex.tree.drf.TreeMeasuresCollector.TreeMeasures

Number of processed row per tree.

_ntrees - Variable in class hex.tree.drf.TreeMeasuresCollector.TreeMeasures

Actual number of trees which votes are stored in this object

_ntrees - Variable in class hex.tree.isoforextended.ExtendedIsolationForestModel.ExtendedIsolationForestOutput

_ntrees - Variable in class hex.tree.isoforextended.ExtendedIsolationForestModel.ExtendedIsolationForestParameters

Number of trees in the forest

_ntrees - Variable in class hex.tree.SharedTree

_ntrees - Variable in class hex.tree.SharedTreeModel.SharedTreeOutput

Number of trees actually in the model (as opposed to requested)

_ntrees - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters

_nullDOF - Variable in class hex.gam.GAMModel

_nullDOF - Variable in class hex.glm.GLMModel

_num_fixed_coeffs - Variable in class hex.hglm.HGLMModel.HGLMModelOutput

_num_iteration_without_new_exemplar - Variable in class hex.aggregator.AggregatorModel.AggregatorParameters

_num_knots - Variable in class hex.gam.GAMModel.GAMParameters

_num_knots_sorted - Variable in class hex.gam.GAMModel.GAMParameters

_num_knots_tp - Variable in class hex.gam.GAMModel.GAMParameters

_num_random_coeffs - Variable in class hex.hglm.HGLMModel.HGLMModelOutput

_num_trees - Variable in class hex.tree.TreeStats

_numBasis - Variable in class hex.gam.MatrixFrameUtils.GenISplineGamOneColumn

_numBasis - Variable in class hex.gam.MatrixFrameUtils.GenMSplineGamOneColumn

_numberOfModels - Variable in class hex.anovaglm.ANOVAGLM

_numberOfPredCombo - Variable in class hex.anovaglm.ANOVAGLM

_numberOfPredictors - Variable in class hex.anovaglm.ANOVAGLM

_numClasses - Variable in class hex.tree.dt.mrtasks.GetClassCountsMRTask

_numcnt - Variable in class hex.glrm.ModelMetricsGLRM

_numcnt - Variable in class hex.glrm.ModelMetricsGLRM.GlrmModelMetricsBuilder

_numerr - Variable in class hex.glrm.ModelMetricsGLRM

_numGAMcols - Variable in class hex.gam.MatrixFrameUtils.AddCSGamColumns

_numGAMCols - Variable in class hex.gam.MatrixFrameUtils.AddISGamColumns

_numGAMCols - Variable in class hex.gam.MatrixFrameUtils.AddMSGamColumns

_numKnots - Variable in class hex.gam.GAMModel.GAMModelOutput

_numKnots - Variable in class hex.gam.MatrixFrameUtils.GenCSSplineGamOneColumn

_numMeans - Variable in class hex.DataInfo

_numNAFill - Variable in class hex.DataInfo

_numNAFills - Variable in class hex.anovaglm.GenerateTransformColumns

_numOffsets - Variable in class hex.DataInfo

_numPredictors - Variable in class hex.modelselection.ModelSelection

_nums - Variable in class hex.DataInfo

_numTrees - Variable in class hex.tree.isoforextended.isolationtree.IsolationTreeStats

_nv - Variable in class hex.svd.SVDModel.SVDParameters

_obj_reg - Variable in class hex.gam.GAMModel.GAMParameters

_obj_reg - Variable in class hex.glm.GLMModel.GLMParameters

_obj_reg - Variable in class hex.modelselection.ModelSelectionModel.ModelSelectionParameters

_objective - Variable in class hex.glrm.GLRMModel.GLRMOutput

_objective - Variable in class hex.pca.PCAModel.PCAOutput

_objective_epsilon - Variable in class hex.gam.GAMModel.GAMParameters

_objective_epsilon - Variable in class hex.glm.GLMModel.GLMParameters

_objective_epsilon - Variable in class hex.modelselection.ModelSelectionModel.ModelSelectionParameters

_objVal - Variable in class hex.optimization.OptimizationUtils.GradientInfo

_offset - Variable in class hex.DataInfo

_offsets - Variable in class hex.grep.GrepModel.GrepOutput

_OneOEPS - Static variable in class hex.glm.GLMModel

_oneOGamColStd - Variable in class hex.gam.GAM

_oneOGamColStd - Variable in class hex.gam.GAMModel.GAMModelOutput

_only_v - Variable in class hex.svd.SVDModel.SVDParameters

_OOBEnabled - Variable in class hex.tree.ReconstructTreeState

_ordinal - Variable in class hex.glm.GLMModel.GLMOutput

_origa - Variable in class hex.deeplearning.Neurons

Layer state (one per neuron): activity, error

_original_model_full_name - Variable in class hex.generic.GenericModelOutput

_original_model_identifier - Variable in class hex.generic.GenericModelOutput

_originalBeta - Variable in class hex.optimization.OptimizationUtils.ExactLineSearch

_originalImplementation - Variable in class hex.util.LinearAlgebraUtils.BMulInPlaceTask

_out_of_bounds - Variable in class hex.isotonic.IsotonicRegressionModel.IsotonicRegressionParameters

_output - Variable in class hex.tree.SharedTreeModelWithContributions.ScoreContributionsTask

_output - Variable in class hex.tree.SharedTreeModelWithContributions.ScoreContributionsWithBackgroundTask

_output - Variable in class hex.tree.SharedTreePojoWriter

_output_frame - Variable in class hex.aggregator.AggregatorModel.AggregatorOutput

_outputSpace - Variable in class hex.tree.SharedTreeModelWithContributions.ScoreContributionsWithBackgroundTask

_overwrite_with_best_model - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

If enabled, store the best model under the destination key of this model at the end of training.

_p_values - Variable in class hex.glm.GLMModel.RegularizationPath

_p_values_threshold - Variable in class hex.modelselection.ModelSelectionModel.ModelSelectionParameters

_parallel_main_model_building - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters

_parms - Variable in class hex.ensemble.Metalearner

_parms - Variable in class hex.glm.ComputationState

_parms - Variable in class hex.hglm.ComputationStateHGLM

_parms - Variable in class hex.tree.DTree

_path - Variable in class hex.generic.GenericModelParameters

Path of the file with embedded model

_pca_implementation - Variable in class hex.pca.PCAModel.PCAParameters

_pca_method - Variable in class hex.aggregator.AggregatorModel.AggregatorParameters

_pca_method - Variable in class hex.pca.PCAModel.PCAParameters

_pcond - Variable in class hex.naivebayes.NaiveBayesModel.NaiveBayesOutput

_pcond_raw - Variable in class hex.naivebayes.NaiveBayesModel.NaiveBayesOutput

_penaltyMat - Variable in class hex.gam.GamSplines.ThinPlateRegressionUtils.ScaleTPPenalty

_penaltyMat - Variable in class hex.gam.MatrixFrameUtils.GenCSSplineGamOneColumn

_penaltyMat - Variable in class hex.gam.MatrixFrameUtils.GenISplineGamOneColumn

_penaltyMat - Variable in class hex.gam.MatrixFrameUtils.GenMSplineGamOneColumn

_penaltyMatrices - Variable in class hex.gam.GAMModel.GAMModelOutput

_penaltyMatricesCenter - Variable in class hex.gam.GAMModel.GAMModelOutput

_penaltyMatrix - Variable in class hex.glm.GLM

_penaltyScale - Variable in class hex.gam.GAM

_penaltyScale - Variable in class hex.gam.GAMModel.GAMModelOutput

_period - Variable in class hex.glrm.GLRMModel.GLRMParameters

_permutation - Variable in class hex.DataInfo

_permutation - Variable in class hex.glrm.GLRMModel.GLRMOutput

_permutation - Variable in class hex.glrm.ModelMetricsGLRM.GlrmModelMetricsBuilder

_permutation - Variable in class hex.pca.PCAModel.PCAOutput

_permutation - Variable in class hex.svd.SVDModel.SVDOutput

_pid - Variable in class hex.tree.DTree.Node

_plug_values - Variable in class hex.anovaglm.ANOVAGLMModel.ANOVAGLMParameters

_plug_values - Variable in class hex.gam.GAMModel.GAMParameters

_plug_values - Variable in class hex.glm.GLMModel.GLMParameters

_plug_values - Variable in class hex.hglm.HGLMModel.HGLMParameters

_plug_values - Variable in class hex.modelselection.ModelSelectionModel.ModelSelectionParameters

_pm - Variable in class hex.optimization.ADMM.L1Solver

_positive_weight - Variable in class hex.psvm.PSVMModel.PSVMParameters

_pre_trained - Variable in class hex.word2vec.Word2VecModel.Word2VecParameters

_pred - Variable in class hex.tree.DTree.LeafNode

_pred1 - Variable in class hex.tree.DHistogram

_pred2 - Variable in class hex.tree.DHistogram

_pred_indicator - Variable in class hex.kmeans.KMeansModel.KMeansParameters

_pred_noise_bandwidth - Variable in class hex.tree.gbm.GBMModel.GBMParameters

_predictions - Variable in class hex.tree.TreeHandler.TreeProperties

_predictor_transform - Variable in class hex.DataInfo

_predictorColumnStart - Variable in class hex.anovaglm.ANOVAGLM

_predictorNames - Variable in class hex.modelselection.ModelSelection

_predictorsAdd - Variable in class hex.modelselection.ModelSelection

_predictorsRemoved - Variable in class hex.modelselection.ModelSelection

_predsAryOffset - Variable in class hex.tree.Score.ScoreIncInfo

_previous - Variable in class hex.deeplearning.Neurons

References for feed-forward connectivity

_prior - Variable in class hex.gam.GAMModel.GAMParameters

_prior - Variable in class hex.glm.GLMModel.GLMParameters

_quasibinomialDomains - Variable in class hex.tree.gbm.GBMModel.GBMOutput

_quiet_mode - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

Enable quiet mode for less output to standard output.

_r2_stopping - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters

_rand - Variable in class hex.tree.DTree

_rand - Variable in class hex.tree.SharedTree

_random_coefficient_names - Variable in class hex.hglm.HGLMModel.HGLMModelOutput

_random_columns - Variable in class hex.glm.GLMModel.GLMParameters

_random_columns - Variable in class hex.hglm.HGLMModel.HGLMParameters

_random_family - Variable in class hex.hglm.HGLMModel.HGLMParameters

_random_intercept - Variable in class hex.hglm.HGLMModel.HGLMParameters

_rank - Variable in class hex.gam.GAMModel

_rank_ratio - Variable in class hex.psvm.PSVMModel.PSVMParameters

_rate - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

When adaptive learning rate is disabled, the magnitude of the weight updates are determined by the user specified learning rate (potentially annealed), and are a function of the difference between the predicted value and the target value.

_rate - Variable in class hex.tree.ReconstructTreeState

_rate_annealing - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

Learning rate annealing reduces the learning rate to "freeze" into local minima in the optimization landscape.

_rate_decay - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

The learning rate decay parameter controls the change of learning rate across layers.

_realFeatureLimits - Variable in class hex.tree.dt.mrtasks.FeaturesLimitsMRTask

_reassigned_count - Variable in class hex.kmeans.KMeansModel.KMeansOutput

_recover_svd - Variable in class hex.glrm.GLRMModel.GLRMParameters

_regex - Variable in class hex.grep.GrepModel.GrepParameters

_regression_influence_diagnostics - Variable in class hex.glm.GLMModel.GLMOutput

_regression_stop - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

The stopping criteria in terms of regression error (MSE) on the training data scoring dataset.

_regularization_x - Variable in class hex.glrm.GLRMModel.GLRMParameters

_regularization_y - Variable in class hex.glrm.GLRMModel.GLRMParameters

_rel_tol_num_exemplars - Variable in class hex.aggregator.AggregatorModel.AggregatorParameters

_remove_collinear_columns - Variable in class hex.anovaglm.ANOVAGLMModel.ANOVAGLMParameters

_remove_collinear_columns - Variable in class hex.gam.GAMModel.GAMParameters

_remove_collinear_columns - Variable in class hex.glm.GLMModel.GLMParameters

_remove_collinear_columns - Variable in class hex.modelselection.ModelSelectionModel.ModelSelectionParameters

_remove_duplicates - Variable in class hex.rulefit.RuleFitModel.RuleFitParameters

_replicate_training_data - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

Replicate the entire training dataset onto every node for faster training on small datasets.

_representation_key - Variable in class hex.glrm.GLRMModel.GLRMOutput

_representation_name - Variable in class hex.glrm.GLRMModel.GLRMOutput

_representation_name - Variable in class hex.glrm.GLRMModel.GLRMParameters

_reproducible - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

Force reproducibility on small data (will be slow - only uses 1 thread)

_reproducible_histos - Variable in class hex.tree.SharedTree.SharedTreeDebugParams

_rescnt - Variable in class hex.naivebayes.NaiveBayesModel.NaiveBayesOutput

_response_column - Variable in class hex.tree.isofor.IsolationForestModel.IsolationForestOutput

_response_domain - Variable in class hex.tree.isofor.IsolationForestModel.IsolationForestOutput

_response_transform - Variable in class hex.DataInfo

_responseDomains - Variable in class hex.gam.GAMModel.GAMModelOutput

_responses - Variable in class hex.DataInfo

_rho - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

The first of two hyper parameters for adaptive learning rate (ADADELTA).

_rho - Variable in class hex.psvm.PSVMModel.PSVMModelOutput

_rightChildren - Variable in class hex.tree.TreeHandler.TreeProperties

_rightCount - Variable in class hex.tree.dt.binning.SplitStatistics

_rightCount0 - Variable in class hex.tree.dt.binning.SplitStatistics

_row - Variable in class hex.FrameTask.ExtractDenseRow

_rule_generation_ntrees - Variable in class hex.rulefit.RuleFitModel.RuleFitParameters

_rule_importance - Variable in class hex.rulefit.RuleFitModel.RuleFitOutput

_s_scale - Variable in class hex.gam.GamSplines.ThinPlateRegressionUtils.ScaleTPPenalty

_s_scale - Variable in class hex.gam.MatrixFrameUtils.GenCSSplineGamOneColumn

_s_scale - Variable in class hex.gam.MatrixFrameUtils.GenISplineGamOneColumn

_s_scale - Variable in class hex.gam.MatrixFrameUtils.GenMSplineGamOneColumn

_sample_rate - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters

_sample_rate_per_class - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters

_sample_size - Variable in class hex.tree.isofor.IsolationForestModel.IsolationForestParameters

_sample_size - Variable in class hex.tree.isoforextended.ExtendedIsolationForestModel.ExtendedIsolationForestOutput

_sample_size - Variable in class hex.tree.isoforextended.ExtendedIsolationForestModel.ExtendedIsolationForestParameters

Number of randomly selected rows from original data before each tree build.

_save_mapping_frame - Variable in class hex.aggregator.AggregatorModel.AggregatorParameters

_save_transformed_framekeys - Variable in class hex.anovaglm.ANOVAGLMModel.ANOVAGLMParameters

_save_v_frame - Variable in class hex.svd.SVDModel.SVDParameters

_savePenaltyMat - Variable in class hex.gam.GAMModel.GAMParameters

_saveZMatrix - Variable in class hex.gam.GAMModel.GAMParameters

_scale - Variable in class hex.gam.GAMModel.GAMParameters

_scale_sorted - Variable in class hex.gam.GAMModel.GAMParameters

_scale_tp_penalty_mat - Variable in class hex.gam.GAMModel.GAMParameters

_score_duty_cycle - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

Maximum fraction of wall clock time spent on model scoring on training and validation samples, and on diagnostics such as computation of feature importances (i.e., not on training).

_score_each_iteration - Variable in class hex.hglm.HGLMModel.HGLMParameters

_score_interval - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

The minimum time (in seconds) to elapse between model scoring.

_score_interval - Variable in class hex.tree.isoforextended.ExtendedIsolationForestModel.ExtendedIsolationForestParameters

After each _score_interval milliseconds - run scoring But limit the scoring time consumption to 10% of whole training time.

_score_interval - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters

_score_iteration_interval - Variable in class hex.glm.GLMModel.GLMParameters

_score_iteration_interval - Variable in class hex.hglm.HGLMModel.HGLMParameters

_score_training_samples - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

The number of training dataset points to be used for scoring.

_score_training_samples - Variable in class hex.ensemble.StackedEnsembleModel.StackedEnsembleParameters

_score_tree_interval - Variable in class hex.tree.isoforextended.ExtendedIsolationForestModel.ExtendedIsolationForestParameters

Score every so many trees (no matter what)

_score_tree_interval - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters

_score_validation_samples - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

The number of validation dataset points to be used for scoring.

_score_validation_sampling - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

Method used to sample the validation dataset for scoring, see Score Validation Samples above.

_scoreCols - Variable in class hex.tree.DTree.UndecidedNode

_scored_train - Variable in class hex.tree.isoforextended.ExtendedIsolationForestModel.ExtendedIsolationForestOutput

_scored_train - Variable in class hex.tree.SharedTreeModel.SharedTreeOutput

_scored_valid - Variable in class hex.tree.SharedTreeModel.SharedTreeOutput

_scoring_history_valid - Variable in class hex.hglm.HGLMModel.HGLMModelOutput

_se_coef - Variable in class hex.coxph.CoxPHModel.CoxPHOutput

_second_diag - Variable in class hex.gam.MatrixFrameUtils.TriDiagonalMatrix

_seed - Variable in class hex.hglm.HGLMModel.HGLMParameters

_seed - Variable in class hex.psvm.PSVMModel.PSVMParameters

_seed - Variable in class hex.tree.DHistogram

_selected_alpha_idx - Variable in class hex.glm.GLMModel.GLMOutput

_selected_lambda_idx - Variable in class hex.glm.GLMModel.GLMOutput

_selected_submodel_idx - Variable in class hex.glm.GLMModel.GLMOutput

_sent_sample_rate - Variable in class hex.word2vec.Word2VecModel.Word2VecParameters

_separate_linear_beta - Variable in class hex.glm.GLMModel.GLMParameters

_sgap_threshold - Variable in class hex.psvm.psvm.PrimalDualIPM.Parms

_showFixedMatVecs - Variable in class hex.hglm.HGLMModel.HGLMParameters

_shuffle - Variable in class hex.FrameTask

_shuffle_training_data - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

Enable shuffling of training data (on each node).

_single_node_mode - Variable in class hex.coxph.CoxPHModel.CoxPHParameters

If true, computation is performed with local jobs.

_single_node_mode - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

Run on a single node for fine-tuning of model parameters.

_singular_vals - Variable in class hex.glrm.GLRMModel.GLRMOutput

_size - Variable in class hex.gam.MatrixFrameUtils.TriDiagonalMatrix

_skip - Variable in class hex.tree.DTreeScorer

_skipMissing - Variable in class hex.DataInfo

_skippedRows - Variable in class hex.glm.TweedieEstimator

_solver - Variable in class hex.anovaglm.ANOVAGLMModel.ANOVAGLMParameters

_solver - Variable in class hex.gam.GAMModel.GAMParameters

_solver - Variable in class hex.glm.GLMModel.GLMParameters

_solver - Variable in class hex.modelselection.ModelSelectionModel.ModelSelectionParameters

_sparse - Variable in class hex.DataInfo.Rows

_sparse - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

_sparse - Variable in class hex.FrameTask

_sparse - Variable in class hex.FrameTask2

_sparsity_beta - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

_splat - Variable in class hex.tree.DTree.DecidedNode

_spline_orders - Variable in class hex.gam.GAMModel.GAMParameters

_spline_orders_sorted - Variable in class hex.gam.GAMModel.GAMParameters

_splines_non_negative - Variable in class hex.gam.GAMModel.GAMParameters

_splines_non_negative_sorted - Variable in class hex.gam.GAMModel.GAMParameters

_split - Variable in class hex.tree.DTree.DecidedNode

_splitCounts - Variable in class hex.tree.isofor.IsolationForest.VarSplits

_splitDepths - Variable in class hex.tree.isofor.IsolationForest.VarSplits

_splittingRule - Variable in class hex.tree.dt.binning.SplitStatistics

_sse - Variable in class hex.hglm.MetricBuilderHGLM

_sse - Variable in class hex.util.LinearAlgebraUtils.ForwardSolve

_st - Variable in class hex.tree.DTreeScorer

_stacking_strategy - Variable in class hex.ensemble.StackedEnsembleModel.StackedEnsembleOutput

_standardize - Variable in class hex.anovaglm.ANOVAGLMModel.ANOVAGLMParameters

_standardize - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

If enabled, automatically standardize the data.

_standardize - Variable in class hex.gam.GAMModel.GAMParameters

_standardize - Variable in class hex.glm.GLMModel.GLMParameters

_standardize - Variable in class hex.kmeans.KMeansModel.KMeansParameters

_standardize - Variable in class hex.modelselection.ModelSelectionModel.ModelSelectionParameters

_standardize_tp_gam_cols - Variable in class hex.gam.GAMModel.GAMParameters

_standardized_coefficient_magnitudes - Variable in class hex.gam.GAMModel.GAMModelOutput

_standardized_model_beta - Variable in class hex.gam.GAMModel.GAMModelOutput

_standardized_model_beta_multinomial - Variable in class hex.gam.GAMModel.GAMModelOutput

_standardized_model_beta_multinomial_no_centering - Variable in class hex.gam.GAMModel.GAMModelOutput

_standardized_model_beta_no_centering - Variable in class hex.gam.GAMModel.GAMModelOutput

_starT - Variable in class hex.gam.GAMModel.GAMModelOutput

_start_column - Variable in class hex.coxph.CoxPHModel.CoxPHParameters

_startTree - Variable in class hex.tree.Score.ScoreIncInfo

_startval - Variable in class hex.gam.GAMModel.GAMParameters

_startval - Variable in class hex.glm.GLMModel.GLMParameters

_std_deviation - Variable in class hex.glrm.GLRMModel.GLRMOutput

_std_deviation - Variable in class hex.pca.PCAModel.PCAOutput

_std_errs - Variable in class hex.glm.GLMModel.RegularizationPath

_stdOverride - Variable in class hex.glm.GLMModel.GLMParameters

_step - Variable in class hex.tree.DHistogram

_step_size - Variable in class hex.glrm.GLRMModel.GLRMOutput

_stop_column - Variable in class hex.coxph.CoxPHModel.CoxPHParameters

_store_knot_locations - Variable in class hex.gam.GAMModel.GAMParameters

_stratify_by - Variable in class hex.coxph.CoxPHModel.CoxPHParameters

_sumOfRowWeights - Variable in class hex.glm.ComputationState.GramGrad

_surrogate_gap_threshold - Variable in class hex.psvm.PSVMModel.PSVMParameters

_sv_threshold - Variable in class hex.psvm.PSVMModel.PSVMParameters

_svd_method - Variable in class hex.glrm.GLRMModel.GLRMParameters

_svd_method - Variable in class hex.svd.SVDModel.SVDParameters

_svs_count - Variable in class hex.psvm.PSVMModel.PSVMModelOutput

_target_num_exemplars - Variable in class hex.aggregator.AggregatorModel.AggregatorParameters

_target_ratio_comm_to_comp - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

_tau_e_var - Variable in class hex.hglm.HGLMModel.HGLMModelOutput

_tau_e_var_init - Variable in class hex.hglm.HGLMModel.HGLMParameters

_tau_u_var_init - Variable in class hex.hglm.HGLMModel.HGLMParameters

_tauEVar - Variable in class hex.hglm.ComputationStateHGLM.ComputationStateSimple

_temp - Variable in class hex.glm.GLMTask.GLMCoordinateDescentTaskSeqIntercept

_temp - Variable in class hex.glm.GLMTask.GLMCoordinateDescentTaskSeqNaive

_theta - Variable in class hex.anovaglm.ANOVAGLMModel.ANOVAGLMParameters

_theta - Variable in class hex.gam.GAMModel.GAMParameters

_theta - Variable in class hex.glm.GLMModel.GLMParameters

_thinPlateSmoothersWithKnotsNum - Variable in class hex.gam.GAMModel

_third_diag - Variable in class hex.gam.MatrixFrameUtils.TriDiagonalMatrix

_thresholds - Variable in class hex.tree.TreeHandler.TreeProperties

_thresholds_x - Variable in class hex.isotonic.IsotonicRegressionModel.IsotonicRegressionOutput

_thresholds_y - Variable in class hex.isotonic.IsotonicRegressionModel.IsotonicRegressionOutput

_ties - Variable in class hex.coxph.CoxPHModel.CoxPHParameters

_timeLastIterationEnter - Variable in class hex.deeplearning.DeepLearningModel

_timeLastScoreStart - Variable in class hex.deeplearning.DeepLearningModel

_tmat - Variable in class hex.hglm.ComputationStateHGLM.ComputationStateSimple

_tmat - Variable in class hex.hglm.HGLMModel.HGLMModelOutput

_tmat - Variable in class hex.hglm.MetricBuilderHGLM

_tot_withinss - Variable in class hex.kmeans.KMeansModel.KMeansOutput

_total_variance - Variable in class hex.glrm.GLRMModel.GLRMOutput

_total_variance - Variable in class hex.pca.PCAModel.PCAOutput

_total_variance - Variable in class hex.svd.SVDModel.SVDOutput

_totalRows - Variable in class hex.glm.TweedieEstimator

_totGamifiedColCentered - Variable in class hex.gam.MatrixFrameUtils.AddISGamColumns

_totGamifiedColCentered - Variable in class hex.gam.MatrixFrameUtils.AddMSGamColumns

_totKnots - Variable in class hex.gam.MatrixFrameUtils.GenISplineGamOneColumn

_totKnots - Variable in class hex.gam.MatrixFrameUtils.GenMSplineGamOneColumn

_totss - Variable in class hex.kmeans.KMeansModel.KMeansOutput

_tradeoff - Variable in class hex.psvm.psvm.PrimalDualIPM.Parms

_train_samples_per_iteration - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

The number of training data rows to be processed per iteration.

_training_time_ms - Variable in class hex.anovaglm.ANOVAGLMModel.ANOVAGLMModelOutput

_training_time_ms - Variable in class hex.glm.GLMModel.GLMOutput

_training_time_ms - Variable in class hex.glrm.GLRMModel.GLRMOutput

_training_time_ms - Variable in class hex.hglm.HGLMModel.HGLMModelOutput

_training_time_ms - Variable in class hex.kmeans.KMeansModel.KMeansOutput

_training_time_ms - Variable in class hex.pca.PCAModel.PCAOutput

_training_time_ms - Variable in class hex.svd.SVDModel.SVDOutput

_training_time_ms - Variable in class hex.tree.isoforextended.ExtendedIsolationForestModel.ExtendedIsolationForestOutput

_training_time_ms - Variable in class hex.tree.SharedTreeModel.SharedTreeOutput

Training time

_trainPredsCache - Variable in class hex.tree.SharedTree

_transform - Variable in class hex.aggregator.AggregatorModel.AggregatorParameters

_transform - Variable in class hex.glrm.GLRMModel.GLRMParameters

_transform - Variable in class hex.pca.PCAModel.PCAParameters

_transform - Variable in class hex.svd.SVDModel.SVDParameters

_transformed_columns_key - Variable in class hex.anovaglm.ANOVAGLMModel.ANOVAGLMModelOutput

_transformedColNames - Variable in class hex.anovaglm.ANOVAGLM

_treatment - Variable in class hex.DataInfo

_tree - Variable in class hex.tree.DTree.Node

_treeDecisionPath - Variable in class hex.tree.TreeHandler.TreeProperties

_treeKey - Variable in class hex.tree.dt.DTModel.DTOutput

_treeKeys - Variable in class hex.tree.CompressedForest

_treeKeys - Variable in class hex.tree.SharedTreeModel.SharedTreeOutput

Trees get big, so store each one separately in the DKV.

_treeKeysAux - Variable in class hex.tree.SharedTreeModel.SharedTreeOutput

_trees - Variable in class hex.tree.CompressedForest.LocalCompressedForest

_trees - Variable in class hex.tree.SharedTreePojoWriter

_treeSHAP - Variable in class hex.tree.SharedTreeModelWithContributions.ScoreContributionsTask

_treeSHAP - Variable in class hex.tree.SharedTreeModelWithContributions.ScoreContributionsWithBackgroundTask

_treeStats - Variable in class hex.tree.SharedTreeModel.SharedTreeOutput

More indepth tree stats

_treeStats - Variable in class hex.tree.SharedTreePojoWriter

_tweedie_epsilon - Variable in class hex.glm.GLMModel.GLMParameters

_tweedie_link_power - Variable in class hex.anovaglm.ANOVAGLMModel.ANOVAGLMParameters

_tweedie_link_power - Variable in class hex.gam.GAMModel.GAMParameters

_tweedie_link_power - Variable in class hex.glm.GLMModel.GLMParameters

_tweedie_link_power - Variable in class hex.modelselection.ModelSelectionModel.ModelSelectionParameters

_tweedie_variance_power - Variable in class hex.anovaglm.ANOVAGLMModel.ANOVAGLMParameters

_tweedie_variance_power - Variable in class hex.gam.GAMModel.GAMParameters

_tweedie_variance_power - Variable in class hex.glm.GLMModel.GLMParameters

_tweedie_variance_power - Variable in class hex.modelselection.ModelSelectionModel.ModelSelectionParameters

_u - Variable in class hex.optimization.ADMM.L1Solver

_u_key - Variable in class hex.svd.SVDModel.SVDOutput

_u_name - Variable in class hex.svd.SVDModel.SVDParameters

_ubeta - Variable in class hex.hglm.ComputationStateHGLM.ComputationStateSimple

_ubeta - Variable in class hex.hglm.HGLMModel.HGLMModelOutput

_ubeta - Variable in class hex.hglm.HGLMTask.ResidualLLHTask

_ubeta - Variable in class hex.hglm.MetricBuilderHGLM

_updates - Variable in class hex.glrm.GLRMModel.GLRMOutput

_uplift_metric - Variable in class hex.tree.uplift.UpliftDRFModel.UpliftDRFParameters

_upliftMetric - Variable in class hex.tree.DHistogram

_use_all_factor_levels - Variable in class hex.aggregator.AggregatorModel.AggregatorParameters

_use_all_factor_levels - Variable in class hex.coxph.CoxPHModel.CoxPHParameters

_use_all_factor_levels - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

_use_all_factor_levels - Variable in class hex.gam.GAMModel.GAMParameters

_use_all_factor_levels - Variable in class hex.glm.GLMModel.GLMParameters

_use_all_factor_levels - Variable in class hex.hglm.HGLMModel.HGLMParameters

_use_all_factor_levels - Variable in class hex.modelselection.ModelSelectionModel.ModelSelectionParameters

_use_all_factor_levels - Variable in class hex.pca.PCAModel.PCAParameters

_use_all_factor_levels - Variable in class hex.svd.SVDModel.SVDParameters

_use_best_cv_iteration - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters

_useAllFactorLevels - Variable in class hex.DataInfo

_useDispersion1 - Variable in class hex.glm.GLMModel.GLMParameters

_useFraction - Variable in class hex.FrameTask

_user_points - Variable in class hex.kmeans.KMeansModel.KMeansParameters

_user_x - Variable in class hex.glrm.GLRMModel.GLRMParameters

_user_y - Variable in class hex.glrm.GLRMModel.GLRMParameters

_useUplift - Variable in class hex.tree.DHistogram

_v - Variable in class hex.svd.SVDModel.SVDOutput

_v_key - Variable in class hex.svd.SVDModel.SVDOutput

_v_name - Variable in class hex.svd.SVDModel.SVDParameters

_valid - Variable in class hex.DataInfo

_validKeys - Variable in class hex.gam.GAMModel

_validPredsCache - Variable in class hex.tree.SharedTree

_validWorkspace - Variable in class hex.tree.SharedTree

_vals - Variable in class hex.tree.DHistogram

_vals_dim - Variable in class hex.tree.DHistogram

_valsDimUplift - Variable in class hex.tree.DHistogram

_valsUplift - Variable in class hex.tree.DHistogram

_var_splits - Variable in class hex.tree.isofor.IsolationForestModel.IsolationForestOutput

_variable_importances - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningModelOutput

_variable_importances - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

Whether to compute variable importances for input features.

_variable_importances - Variable in class hex.gam.GAMModel.GAMModelOutput

_variable_importances - Variable in class hex.generic.GenericModelOutput

_variable_importances - Variable in class hex.glm.GLMModel.GLMOutput

_variable_importances - Variable in class hex.tree.SharedTreeModel.SharedTreeOutput

Variable importances computed during training

_variable_splits - Variable in class hex.tree.isofor.IsolationForestModel.IsolationForestOutput

_varimp - Variable in class hex.gam.GAMModel.GAMModelOutput

_varimp - Variable in class hex.glm.GLMModel.GLMOutput

_varimp - Variable in class hex.tree.SharedTreeModel.SharedTreeOutput

_vec_size - Variable in class hex.word2vec.Word2VecModel.Word2VecParameters

_vecs - Variable in class hex.word2vec.Word2VecModel.Word2VecOutput

_vecSize - Variable in class hex.word2vec.Word2VecModel.Word2VecOutput

_verbose - Variable in class hex.glrm.GLRMModel.GLRMParameters

_vocab - Variable in class hex.word2vec.Word2VecModel.Word2VecOutput

_w - Variable in class hex.deeplearning.Neurons

_wEA - Variable in class hex.deeplearning.Neurons

_weak_learner - Variable in class hex.adaboost.AdaBoostModel.AdaBoostParameters

Choose a weak learner type.

_weak_learner_params - Variable in class hex.adaboost.AdaBoostModel.AdaBoostParameters

Custom _weak_learner parameters.

_weights - Variable in class hex.DataInfo

_window_size - Variable in class hex.word2vec.Word2VecModel.Word2VecParameters

_withinss - Variable in class hex.kmeans.KMeansModel.KMeansOutput

_word_model - Variable in class hex.word2vec.Word2VecModel.Word2VecParameters

_words - Variable in class hex.word2vec.Word2VecModel.Word2VecOutput

_workspaceColCnt - Variable in class hex.tree.Score.ScoreIncInfo

_workspaceColIdx - Variable in class hex.tree.Score.ScoreIncInfo

_x_epsilon - Variable in class hex.psvm.psvm.PrimalDualIPM.Parms

_x_factor_key - Variable in class hex.glrm.GLRMModel.GLRMOutput

_xx - Variable in class hex.gram.Gram

_xx - Variable in class hex.gram.Gram.Cholesky

_xxCache - Variable in class hex.gram.Gram

_xy - Variable in class hex.glm.ComputationState.GramGrad

_xy - Variable in class hex.glm.GLMTask.LSTask

_yMinusFixPredSquare - Variable in class hex.hglm.HGLMModel.HGLMModelOutput

_yMinusFixPredSquare - Variable in class hex.hglm.MetricBuilderHGLM

_yMinusFixPredSquareValid - Variable in class hex.hglm.HGLMModel.HGLMModelOutput

_yMinusXTimesZ - Variable in class hex.hglm.HGLMModel.HGLMModelOutput

_yMinusXTimesZ - Variable in class hex.hglm.HGLMScore

_yMinusXTimesZValid - Variable in class hex.hglm.HGLMModel.HGLMModelOutput

_ymu - Variable in class hex.gam.GAMModel

_ymu - Variable in class hex.glm.GLMModel

_ySigma - Variable in class hex.glm.GLMModel

_z_coef - Variable in class hex.coxph.CoxPHModel.CoxPHOutput

_z_values - Variable in class hex.glm.GLMModel.RegularizationPath

_zero_threshold - Variable in class hex.psvm.PSVMModel.PSVMParameters

_ZTransp - Variable in class hex.gam.MatrixFrameUtils.GenCSSplineGamOneColumn

_ZTransp - Variable in class hex.gam.MatrixFrameUtils.GenMSplineGamOneColumn

_zTranspose - Variable in class hex.gam.GAMModel.GAMModelOutput

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