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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
 
addWdataZiEtaOld2Response() - Method in class hex.glm.GLM.GLMDriver
Internal H2O method.
adjustGradient(double[], double[]) - Method in class hex.glm.GLM.BetaConstraint
 
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.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.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.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
 
buildGammaGLM(Frame, Frame, int[], long, long, boolean) - Method in class hex.glm.GLM.GLMDriver
This method will generate a training frame according to HGLM doc, build a gamma GLM model with dispersion parameter set to 1 if enabled and calcluate the p-value if enabled.
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.
buildRandomCoefficients2DTable(double[], String[]) - Method in class hex.schemas.GLMModelV3.GLMModelOutputV3
 
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
 
calculate_all_beta(double[], Frame, Frame, int, double[][]) - Method in class hex.glm.GLM.GLMDriver
This method will estimate beta and ubeta using QR decomposition.
CalculateAugZW(Job, DataInfo, GLMModel.GLMParameters, Frame, int, int, int) - Constructor for class hex.glm.GLMTask.CalculateAugZW
 
CalculateAugZWData(Job, DataInfo, int) - Constructor for class hex.glm.GLMTask.CalculateAugZWData
 
CalculateAugZWRandCols(Job, Frame, int, long) - Constructor for class hex.glm.GLMTask.CalculateAugZWRandCols
 
calculateConstraintSquare(ComputationState, ConstrainedGLMUtils.LinearConstraints[], ConstrainedGLMUtils.LinearConstraints[]) - Static method in class hex.glm.ConstrainedGLMUtils
 
CalculateEtaInfo(int[]) - Constructor for class hex.glm.GLMTask.CalculateEtaInfo
 
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
 
calculateNewWAugXZ(Frame, int[]) - Method in class hex.glm.GLM.GLMDriver
 
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
 
CalculateW4Data(Job, DataInfo, GLMModel.GLMParameters, int[], double[], double[], double[], double[], double, double) - Constructor for class hex.glm.GLMTask.CalculateW4Data
 
CalculateW4Rand(Job, GLMModel.GLMParameters, int[], double[], double[], double[]) - Constructor for class hex.glm.GLMTask.CalculateW4Rand
 
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
 
calDev(boolean, int[], int, Chunk[], Chunk[], int, GLMModel.GLMWeightsFun, GLMModel.GLMWeightsFun[], double[], double[]) - Method in class hex.glm.GLMTask.ReturnGLMMMERunInfo
 
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
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
 
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
 
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.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
 
checkIterationDone(double[], GLM.GLMGradientInfo, int) - Method in class hex.glm.GLM.GLMDriver
This method will first check if enough progress has been made with progress method.
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
 
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
 
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
 
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.
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
 
copy2DArray(double[][], double[][]) - Static method in class hex.gam.MatrixFrameUtils.GamUtils
 
copy2DArray(double[][]) - Static method in class hex.gam.MatrixFrameUtils.GamUtils
 
copy2DArray(int[][], int[][]) - Static method in class hex.gam.MatrixFrameUtils.GamUtils
 
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
 
copyOver(double[][], double[][]) - Method in class hex.glm.GLM.GLMDriver
 
CopyPartsOfFrame(Frame, int[], int[], long) - Constructor for class hex.glm.GLMTask.CopyPartsOfFrame
 
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
 
copyUserInitialValues(int, int, double[], double[], double[], double, double[], Frame, String[]) - Method in class hex.glm.GLM
This method performs a simple copying of user provided initial values to parameters - beta, ubeta, phi, tau, psi, init_sig_u
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.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.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.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
 
DataAddW2AugXZ(Job, DataInfo, int[]) - Constructor for class hex.glm.GLMTask.DataAddW2AugXZ
 
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
 
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
 
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
 
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
 
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
 
ExpandRandomColumns(Job, int[], int[], int) - Constructor for class hex.glm.GLMTask.ExpandRandomColumns
 
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
 
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
 
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
 
ExtractFrameFromSourceWithProcess(Frame, int[], long, long) - Constructor for class hex.glm.GLMTask.ExtractFrameFromSourceWithProcess
 
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.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.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(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
 
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
 
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.
findCatMinZVal(GLMModel, List<Double>) - Static method in class hex.modelselection.ModelSelectionUtils
This method extracts the categorical coefficient 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.
findRandColIndex(int[], long) - Static method in class hex.glm.GLMTask.CalculateW4Rand
Given colIndex to the expanded random columns, this method will calculate which random column that colIndex belongs to.
findRandColIndex(int[], long) - Static method in class hex.glm.GLMTask.RandColAddW2AugXZ
Given colIndex to the expanded random columns, this method will calculate which random column that colIndex belongs to.
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
 
fitDataDispersion(Frame, int[], double[]) - Method in class hex.glm.GLM.GLMDriver
This method estimates the init_sig_e by building a gamma GLM with response
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.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
 
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
 
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.
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
 
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
 
GenerateResid(Job, double, int, int, long) - Constructor for class hex.glm.GLMTask.GenerateResid
 
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
 
generateSummaryHGLM(Key, int) - Method in class hex.glm.GLMModel
This one is for HGLM
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_correction_HL() - Method in class hex.glm.ComputationState
 
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_phi() - Method in class hex.glm.ComputationState
 
get_priorw_wpsi() - Method in class hex.glm.ComputationState
 
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_psi() - Method in class hex.glm.ComputationState
 
get_tau() - Method in class hex.glm.ComputationState
 
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
 
getAllChunks(Frame, int, Chunk[], int[]) - Static method in class hex.glm.GLMTask.DataAddW2AugXZ
Given the chkIdx, this method will fetch the chunks with columns specified in vecIdx
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
 
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
 
getCorrectChunk(Frame, int, long, Chunk[], int[], int[]) - Static method in class hex.glm.GLMTask.DataAddW2AugXZ
This method, given the absolute row index of interest, will grab the correct chunk from augXZ containing the same absolute row index of interest.
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.
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
 
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
 
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.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
 
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
 
getOneSingleChunk(Frame, int, long, Chunk[], int[]) - Static method in class hex.glm.GLMTask.DataAddW2AugXZ
Given the absolute row index of interest, this method will find the chunk index of augXZ that contains the absolute row index
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
 
getRandGLMFuns(GLMModel.GLMWeightsFun[], int, GLMModel.GLMParameters) - Static method in class hex.glm.GLMTask.ReturnGLMMMERunInfo
 
getRandGLMFuns(GLMModel.GLMWeightsFun[], int, GLMModel.GLMParameters) - Static method in class hex.glm.GLMTask.ReturnGLMMMERunInfoRandCols
 
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
 
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
 
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
 
GLMIterationTask(Key, DataInfo, GLMModel.GLMWeightsFun, double[], int, boolean) - 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.CalculateAugZW - Class in hex.glm
 
GLMTask.CalculateAugZWData - Class in hex.glm
 
GLMTask.CalculateAugZWRandCols - Class in hex.glm
 
GLMTask.CalculateEtaInfo - Class in hex.glm
 
GLMTask.CalculateW4Data - Class in hex.glm
This class given the weights generated and stored in _dinfo and wpsi, will multiply the weights to AugXZ and store them in AugXZ.
GLMTask.CalculateW4Rand - Class in hex.glm
This class calculates wpsi, zmi for frame _prior_weights_psi.
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.CopyPartsOfFrame - Class in hex.glm
This class will copy columns from a source frame to columns in the destination frame
GLMTask.DataAddW2AugXZ - Class in hex.glm
This class will update the frame AugXZ which contains Ta*sqrt(W inverse) from documentation: - multiply the generated weight value to Ta and store in AugXZ;
GLMTask.ExpandRandomColumns - Class in hex.glm
 
GLMTask.ExtractFrameFromSourceWithProcess - Class in hex.glm
 
GLMTask.GenerateResid - 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.HelpercAIC - Class in hex.glm
 
GLMTask.LSTask - Class in hex.glm
Task to compute t(X) %*% W %*% X and t(X) %*% W %*% y
GLMTask.RandColAddW2AugXZ - Class in hex.glm
 
GLMTask.ReturnGLMMMERunInfo - Class in hex.glm
 
GLMTask.ReturnGLMMMERunInfoData - Class in hex.glm
fill in the returnFrame from the data portion only
GLMTask.ReturnGLMMMERunInfoRandCols - Class in hex.glm
 
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
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
 
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
 
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.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.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
 
HelpercAIC(boolean, double) - Constructor for class hex.glm.GLMTask.HelpercAIC
 
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.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 - Variable in class hex.schemas.GLMV3.GLMParametersV3
 
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.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.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_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
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.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.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
 
lfv_du_dv(GLMModel.GLMParameters.Family[], GLMModel.GLMParameters.Link[], double[], double[]) - Method in class hex.glm.GLM.GLMDriver
 
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
 
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
 
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.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.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) - 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.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
 
makeZeroOrOneFrame(long, int, int, String[]) - Method in class hex.glm.GLM.GLMDriver
 
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.CalculateAugZW
 
map(Chunk[]) - Method in class hex.glm.GLMTask.CalculateAugZWData
 
map(Chunk[]) - Method in class hex.glm.GLMTask.CalculateAugZWRandCols
 
map(Chunk[]) - Method in class hex.glm.GLMTask.CalculateEtaInfo
 
map(Chunk[]) - Method in class hex.glm.GLMTask.CalculateW4Data
 
map(Chunk[]) - Method in class hex.glm.GLMTask.CalculateW4Rand
 
map(Chunk[]) - Method in class hex.glm.GLMTask.CopyPartsOfFrame
 
map(Chunk[]) - Method in class hex.glm.GLMTask.DataAddW2AugXZ
 
map(Chunk[]) - Method in class hex.glm.GLMTask.ExpandRandomColumns
 
map(Chunk[]) - Method in class hex.glm.GLMTask.ExtractFrameFromSourceWithProcess
 
map(Chunk[]) - Method in class hex.glm.GLMTask.GenerateResid
 
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.HelpercAIC
 
map(Chunk[]) - Method in class hex.glm.GLMTask.RandColAddW2AugXZ
 
map(Chunk[]) - Method in class hex.glm.GLMTask.ReturnGLMMMERunInfo
 
map(Chunk[]) - Method in class hex.glm.GLMTask.ReturnGLMMMERunInfoData
 
map(Chunk[]) - Method in class hex.glm.GLMTask.ReturnGLMMMERunInfoRandCols
 
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[]) - 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.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.
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
 
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.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.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.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[], 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.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.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.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