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A

AbstractPrediction - Class in hex.genmodel.easy.prediction
Predictions from generated models for individual new data points derive from this class.
AbstractPrediction() - Constructor for class hex.genmodel.easy.prediction.AbstractPrediction
 
ActivationUtils - Class in hex.genmodel.algos.deeplearning
 
ActivationUtils() - Constructor for class hex.genmodel.algos.deeplearning.ActivationUtils
 
ActivationUtils.ActivationFunctions - Interface in hex.genmodel.algos.deeplearning
 
ActivationUtils.ExpRectifierDropoutOut - Class in hex.genmodel.algos.deeplearning
 
ActivationUtils.ExpRectifierOut - Class in hex.genmodel.algos.deeplearning
 
ActivationUtils.LinearOut - Class in hex.genmodel.algos.deeplearning
 
ActivationUtils.MaxoutDropoutOut - Class in hex.genmodel.algos.deeplearning
 
ActivationUtils.MaxoutOut - Class in hex.genmodel.algos.deeplearning
 
ActivationUtils.RectifierDropoutOut - Class in hex.genmodel.algos.deeplearning
 
ActivationUtils.RectifierOut - Class in hex.genmodel.algos.deeplearning
 
ActivationUtils.SoftmaxOut - Class in hex.genmodel.algos.deeplearning
 
ActivationUtils.TanhDropoutOut - Class in hex.genmodel.algos.deeplearning
 
ActivationUtils.TanhOut - Class in hex.genmodel.algos.deeplearning
 
add(double, HashMap<String, String[]>) - Static method in class hex.genmodel.GenMunger
 
applyCoefficients(double[], double[], int) - Method in class hex.genmodel.algos.glm.GlmMojoModel
Applies GLM coefficients to a given row of data to calculate feature contributions.
applyDropout(double[], double, int) - Static method in class hex.genmodel.algos.deeplearning.ActivationUtils
 
ArrayUtils - Class in hex.genmodel.utils
Copied (partially) from water.util.ArrayUtils
ArrayUtils() - Constructor for class hex.genmodel.utils.ArrayUtils
 
asnumeric(String, HashMap<String, String[]>) - Static method in class hex.genmodel.GenMunger
 
AutoEncoderModelPrediction - Class in hex.genmodel.easy.prediction
Data reconstructed by the AutoEncoder model based on a given input.
AutoEncoderModelPrediction() - Constructor for class hex.genmodel.easy.prediction.AutoEncoderModelPrediction
 

B

BinomialModelPrediction - Class in hex.genmodel.easy.prediction
Binomial classification model prediction.
BinomialModelPrediction() - Constructor for class hex.genmodel.easy.prediction.BinomialModelPrediction
 
bitSetContains(byte[], int, int, double) - Static method in class hex.genmodel.GenModel
 
bitSetIsInRange(int, int, double) - Static method in class hex.genmodel.GenModel
 
buildNet(ImageDataSet, RuntimeOptions, BackendParams, int, String) - Method in class hex.genmodel.algos.deepwater.caffe.DeepwaterCaffeBackend
 
ByteBufferWrapper - Class in hex.genmodel.utils
Simplified version and drop-in replacement of water.util.AutoBuffer
ByteBufferWrapper(byte[]) - Constructor for class hex.genmodel.utils.ByteBufferWrapper
Read from a fixed byte[]; should not be closed.

C

CAFFE_DIR - Static variable in class hex.genmodel.algos.deepwater.caffe.DeepwaterCaffeBackend
 
CAFFE_H2O_DIR - Static variable in class hex.genmodel.algos.deepwater.caffe.DeepwaterCaffeBackend
 
calibrateClassProbabilities(double[]) - Method in class hex.genmodel.algos.tree.SharedTreeMojoModel
 
calibrateClassProbabilities(double[]) - Method in class hex.genmodel.GenModel
Subclasses implement calibration of class probabilities.
calibratedClassProbabilities - Variable in class hex.genmodel.easy.prediction.BinomialModelPrediction
Class probabilities calibrated by Platt Scaling.
classProbabilities - Variable in class hex.genmodel.easy.prediction.BinomialModelPrediction
This array of length two has the class probability for each class (aka categorical or factor level) in the response column.
classProbabilities - Variable in class hex.genmodel.easy.prediction.MultinomialModelPrediction
This array has an element for each class (aka categorical or factor level) in the response column.
classProbabilities - Variable in class hex.genmodel.easy.prediction.OrdinalModelPrediction
This array has an element for each class (aka categorical or factor level) in the response column.
clear() - Method in class hex.genmodel.algos.deepwater.caffe.nano.Deepwater.Cmd
 
clear() - Method in class hex.genmodel.algos.deepwater.caffe.nano.Deepwater.Saved
 
close() - Method in class hex.genmodel.InMemoryMojoReaderBackend
 
close() - Method in class hex.genmodel.TmpMojoReaderBackend
 
cluster - Variable in class hex.genmodel.easy.prediction.ClusteringModelPrediction
Chosen cluster for this data point.
ClusteringModelPrediction - Class in hex.genmodel.easy.prediction
Clustering model prediction.
ClusteringModelPrediction() - Constructor for class hex.genmodel.easy.prediction.ClusteringModelPrediction
 
Cmd() - Constructor for class hex.genmodel.algos.deepwater.caffe.nano.Deepwater.Cmd
 
columnName - Variable in exception hex.genmodel.easy.exception.PredictUnknownCategoricalLevelException
 
compareTo(Object) - Method in class hex.genmodel.easy.prediction.SortedClassProbability
Comparison implementation for this object type.
computeSerializedSize() - Method in class hex.genmodel.algos.deepwater.caffe.nano.Deepwater.Cmd
 
computeSerializedSize() - Method in class hex.genmodel.algos.deepwater.caffe.nano.Deepwater.Saved
 
Config() - Constructor for class hex.genmodel.easy.EasyPredictModelWrapper.Config
 
contains(int) - Method in class hex.genmodel.utils.GenmodelBitSet
 
contains0(int) - Method in class hex.genmodel.utils.GenmodelBitSet
 
convertDouble2Float(double[]) - Static method in class hex.genmodel.GenModel
 
correctProbabilities(double[], double[], double[]) - Static method in class hex.genmodel.GenModel
Correct a given list of class probabilities produced as a prediction by a model back to prior class distribution
cos(double, HashMap<String, String[]>) - Static method in class hex.genmodel.GenMunger
 
CountingErrorConsumer - Class in hex.genmodel.easy.error
An implementation of EasyPredictModelWrapper.ErrorConsumer counting number of each kind of error even received
CountingErrorConsumer(GenModel) - Constructor for class hex.genmodel.easy.error.CountingErrorConsumer
 
countmatches(String, HashMap<String, String[]>) - Static method in class hex.genmodel.GenMunger
 
Create - Static variable in interface hex.genmodel.algos.deepwater.caffe.nano.Deepwater
 
createActFuns(String) - Method in class hex.genmodel.algos.deeplearning.NeuralNetwork
 
createAuxKey(String) - Static method in class hex.genmodel.GenModel
 
createDeepWaterBackend(String) - Static method in class hex.genmodel.algos.deepwater.DeepwaterMojoModel
 
createReaderBackend(String) - Static method in class hex.genmodel.MojoReaderBackendFactory
 
createReaderBackend(File) - Static method in class hex.genmodel.MojoReaderBackendFactory
 
createReaderBackend(URL, MojoReaderBackendFactory.CachingStrategy) - Static method in class hex.genmodel.MojoReaderBackendFactory
 
createReaderBackend(InputStream, MojoReaderBackendFactory.CachingStrategy) - Static method in class hex.genmodel.MojoReaderBackendFactory
 
cut(double, HashMap<String, String[]>) - Static method in class hex.genmodel.GenMunger
 

D

data - Variable in class hex.genmodel.algos.deepwater.caffe.nano.Deepwater.Cmd
 
dataTransformError(String, Object, String) - Method in class hex.genmodel.easy.EasyPredictModelWrapper.ErrorConsumer
Observe transformation error for data from the predicted dataset.
dataTransformError(String, Object, String) - Method in class hex.genmodel.easy.error.CountingErrorConsumer
 
dataTransformError(String, Object, String) - Method in class hex.genmodel.easy.error.VoidErrorConsumer
 
DeeplearningMojoModel - Class in hex.genmodel.algos.deeplearning
 
DeeplearningMojoModel.StoreWeightsBias - Class in hex.genmodel.algos.deeplearning
 
DeeplearningMojoReader - Class in hex.genmodel.algos.deeplearning
 
DeeplearningMojoReader() - Constructor for class hex.genmodel.algos.deeplearning.DeeplearningMojoReader
 
Deepwater - Interface in hex.genmodel.algos.deepwater.caffe.nano
 
Deepwater.Cmd - Class in hex.genmodel.algos.deepwater.caffe.nano
 
Deepwater.Saved - Class in hex.genmodel.algos.deepwater.caffe.nano
 
DeepwaterCaffeBackend - Class in hex.genmodel.algos.deepwater.caffe
This backend forward requests to a docker images running the python Caffe interface.
DeepwaterCaffeBackend() - Constructor for class hex.genmodel.algos.deepwater.caffe.DeepwaterCaffeBackend
 
DeepwaterCaffeModel - Class in hex.genmodel.algos.deepwater.caffe
 
DeepwaterCaffeModel(int, int[], String[], double[], long, boolean) - Constructor for class hex.genmodel.algos.deepwater.caffe.DeepwaterCaffeModel
 
DeepwaterCaffeModel(String, int[], long, boolean) - Constructor for class hex.genmodel.algos.deepwater.caffe.DeepwaterCaffeModel
 
DeepwaterMojoModel - Class in hex.genmodel.algos.deepwater
 
DeepwaterMojoReader - Class in hex.genmodel.algos.deepwater
 
DeepwaterMojoReader() - Constructor for class hex.genmodel.algos.deepwater.DeepwaterMojoReader
 
delete(BackendModel) - Method in class hex.genmodel.algos.deepwater.caffe.DeepwaterCaffeBackend
 
deleteSavedModel(String) - Method in class hex.genmodel.algos.deepwater.caffe.DeepwaterCaffeBackend
 
deleteSavedParam(String) - Method in class hex.genmodel.algos.deepwater.caffe.DeepwaterCaffeBackend
 
dimensions - Variable in class hex.genmodel.easy.prediction.DimReductionModelPrediction
 
DimReductionModelPrediction - Class in hex.genmodel.easy.prediction
TODO
DimReductionModelPrediction() - Constructor for class hex.genmodel.easy.prediction.DimReductionModelPrediction
 
distances(double[], double[]) - Method in class hex.genmodel.algos.kmeans.KMeansMojoModel
 
distances - Variable in class hex.genmodel.easy.prediction.ClusteringModelPrediction
(Optional) Vector of squared distances to all cluster centers.
distances(double[], double[]) - Method in interface hex.genmodel.IClusteringModel
Calculates squared distances to all cluster centers.
DistributionFamily - Enum in hex.genmodel.utils
Used to be `hex.Distribution.Family`.
divide(double, HashMap<String, String[]>) - Static method in class hex.genmodel.GenMunger
 
domainMap - Variable in class hex.genmodel.easy.EasyPredictModelWrapper
 
DrfMojoModel - Class in hex.genmodel.algos.drf
"Distributed Random Forest" MojoModel
DrfMojoModel(String[], String[][], String) - Constructor for class hex.genmodel.algos.drf.DrfMojoModel
 
DrfMojoReader - Class in hex.genmodel.algos.drf
 
DrfMojoReader() - Constructor for class hex.genmodel.algos.drf.DrfMojoReader
 
dropoutRatios - Variable in class hex.genmodel.algos.deepwater.caffe.nano.Deepwater.Cmd
 

E

EasyPredictModelWrapper - Class in hex.genmodel.easy
An easy-to-use prediction wrapper for generated models.
EasyPredictModelWrapper(EasyPredictModelWrapper.Config) - Constructor for class hex.genmodel.easy.EasyPredictModelWrapper
Create a wrapper for a generated model.
EasyPredictModelWrapper(GenModel) - Constructor for class hex.genmodel.easy.EasyPredictModelWrapper
Create a wrapper for a generated model.
EasyPredictModelWrapper.Config - Class in hex.genmodel.easy
Configuration builder for instantiating a Wrapper.
EasyPredictModelWrapper.ErrorConsumer - Class in hex.genmodel.easy
Observer interface with methods corresponding to errors during the prediction.
emptyArray() - Static method in class hex.genmodel.algos.deepwater.caffe.nano.Deepwater.Cmd
 
emptyArray() - Static method in class hex.genmodel.algos.deepwater.caffe.nano.Deepwater.Saved
 
equalsWithinRecSumErr(double, double, int, double) - Static method in class hex.genmodel.utils.MathUtils
 
ErrorConsumer() - Constructor for class hex.genmodel.easy.EasyPredictModelWrapper.ErrorConsumer
 
escapeNewlines(String) - Static method in class hex.genmodel.utils.StringEscapeUtils
Escapes new line characters of a given string.
escapeQuotes(String) - Static method in class hex.genmodel.algos.tree.SharedTreeNode
 
eval(double[], double, int) - Method in interface hex.genmodel.algos.deeplearning.ActivationUtils.ActivationFunctions
 
eval(double[], double, int) - Method in class hex.genmodel.algos.deeplearning.ActivationUtils.ExpRectifierDropoutOut
 
eval(double[], double, int) - Method in class hex.genmodel.algos.deeplearning.ActivationUtils.ExpRectifierOut
 
eval(double[], double, int) - Method in class hex.genmodel.algos.deeplearning.ActivationUtils.LinearOut
 
eval(double[], double, int) - Method in class hex.genmodel.algos.deeplearning.ActivationUtils.MaxoutDropoutOut
 
eval(double[], double, int) - Method in class hex.genmodel.algos.deeplearning.ActivationUtils.MaxoutOut
 
eval(double[], double, int) - Method in class hex.genmodel.algos.deeplearning.ActivationUtils.RectifierDropoutOut
 
eval(double[], double, int) - Method in class hex.genmodel.algos.deeplearning.ActivationUtils.RectifierOut
 
eval(double[], double, int) - Method in class hex.genmodel.algos.deeplearning.ActivationUtils.SoftmaxOut
 
eval(double[], double, int) - Method in class hex.genmodel.algos.deeplearning.ActivationUtils.TanhDropoutOut
 
eval(double[], double, int) - Method in class hex.genmodel.algos.deeplearning.ActivationUtils.TanhOut
 
exists(String) - Method in class hex.genmodel.InMemoryMojoReaderBackend
 
exists(String) - Method in class hex.genmodel.ModelMojoReader
 
exists(String) - Method in interface hex.genmodel.MojoReaderBackend
 
exp(double) - Static method in enum hex.genmodel.utils.DistributionFamily
 
ExpRectifierDropoutOut() - Constructor for class hex.genmodel.algos.deeplearning.ActivationUtils.ExpRectifierDropoutOut
 
ExpRectifierOut() - Constructor for class hex.genmodel.algos.deeplearning.ActivationUtils.ExpRectifierOut
 
expString(String) - Static method in enum hex.genmodel.utils.DistributionFamily
 
extractLayer(BackendModel, String, float[]) - Method in class hex.genmodel.algos.deepwater.caffe.DeepwaterCaffeBackend
 

F

Failure - Static variable in interface hex.genmodel.algos.deepwater.caffe.nano.Deepwater
 
fill(byte[], int, int, int) - Method in class hex.genmodel.utils.GenmodelBitSet
 
fill2(byte[], ByteBufferWrapper) - Method in class hex.genmodel.utils.GenmodelBitSet
 
fill3(byte[], ByteBufferWrapper) - Method in class hex.genmodel.utils.GenmodelBitSet
 
fill3_1(byte[], ByteBufferWrapper) - Method in class hex.genmodel.utils.GenmodelBitSet
 
fill_1(byte[], int, int, int) - Method in class hex.genmodel.utils.GenmodelBitSet
 
fillDefault(String[]) - Method in class hex.genmodel.GenMunger
 
fillRawData(RowData, double[]) - Method in class hex.genmodel.easy.EasyPredictModelWrapper
 
fit(RowData) - Method in class hex.genmodel.GenMunger
 
formNNInputs() - Method in class hex.genmodel.algos.deeplearning.NeuralNetwork
 
formNNInputsMaxOut() - Method in class hex.genmodel.algos.deeplearning.NeuralNetwork
 
fprop1Layer() - Method in class hex.genmodel.algos.deeplearning.NeuralNetwork
 

G

GBM_rescale(double[]) - Static method in class hex.genmodel.GenModel
 
GbmMojoModel - Class in hex.genmodel.algos.gbm
"Gradient Boosting Machine" MojoModel
GbmMojoModel(String[], String[][], String) - Constructor for class hex.genmodel.algos.gbm.GbmMojoModel
 
GbmMojoReader - Class in hex.genmodel.algos.gbm
 
GbmMojoReader() - Constructor for class hex.genmodel.algos.gbm.GbmMojoReader
 
GenModel - Class in hex.genmodel
This is a helper class to support Java generated models.
GenModel(String[], String[][], String) - Constructor for class hex.genmodel.GenModel
 
GenModel(String[], String[][]) - Constructor for class hex.genmodel.GenModel
Deprecated.
This constructor is deprecated and will be removed in a future version. use GenModel.GenModel(String[] names, String[][] domains, String responseColumn)() instead.
GenmodelBitSet - Class in hex.genmodel.utils
GenmodelBitSet - bitset that "lives" on top of an external byte array.
GenmodelBitSet(int) - Constructor for class hex.genmodel.utils.GenmodelBitSet
 
GenmodelBitSet(int, int) - Constructor for class hex.genmodel.utils.GenmodelBitSet
 
GenMunger - Class in hex.genmodel
 
GenMunger() - Constructor for class hex.genmodel.GenMunger
 
GenMunger.Step<T> - Class in hex.genmodel
 
get1U() - Method in class hex.genmodel.utils.ByteBufferWrapper
 
get2() - Method in class hex.genmodel.utils.ByteBufferWrapper
 
get3() - Method in class hex.genmodel.utils.ByteBufferWrapper
 
get4() - Method in class hex.genmodel.utils.ByteBufferWrapper
 
get4f() - Method in class hex.genmodel.utils.ByteBufferWrapper
 
get8d() - Method in class hex.genmodel.utils.ByteBufferWrapper
 
getBinaryFile(String) - Method in class hex.genmodel.InMemoryMojoReaderBackend
 
getBinaryFile(String) - Method in interface hex.genmodel.MojoReaderBackend
 
getBs() - Method in class hex.genmodel.algos.tree.SharedTreeNode
 
getColIdx(String) - Method in class hex.genmodel.GenModel
Returns index of a column with given name, or -1 if the column is not found.
getColIdx(String) - Method in interface water.genmodel.IGeneratedModel
Returns index of column with give name or -1 if column is not found.
getColName() - Method in class hex.genmodel.algos.tree.SharedTreeNode
 
getColumnName() - Method in exception hex.genmodel.easy.exception.PredictUnknownCategoricalLevelException
Get the column name for which the unknown level was given as input.
getConvertInvalidNumbersToNa() - Method in class hex.genmodel.easy.EasyPredictModelWrapper.Config
 
getConvertUnknownCategoricalLevelsToNa() - Method in class hex.genmodel.easy.EasyPredictModelWrapper.Config
 
getDataTransformationErrorsCount() - Method in class hex.genmodel.easy.error.CountingErrorConsumer
 
getDecisionPath(double) - Static method in class hex.genmodel.algos.tree.SharedTreeMojoModel
 
getDepth() - Method in class hex.genmodel.algos.tree.SharedTreeNode
 
getDomainValues() - Method in class hex.genmodel.algos.tree.SharedTreeNode
 
getDomainValues(String) - Method in class hex.genmodel.GenModel
Gets domain of the given column.
getDomainValues(int) - Method in class hex.genmodel.GenModel
Returns domain values for the i-th column.
getDomainValues() - Method in class hex.genmodel.GenModel
Returns domain values for all columns, including the response column.
getDomainValues(String) - Method in interface water.genmodel.IGeneratedModel
Gets domain of given column.
getDomainValues(int) - Method in interface water.genmodel.IGeneratedModel
Returns domain values for i-th column.
getDomainValues() - Method in interface water.genmodel.IGeneratedModel
Returns domain values for all columns including response column.
getErrorConsumer() - Method in class hex.genmodel.easy.EasyPredictModelWrapper.Config
 
getHeader() - Method in class hex.genmodel.easy.EasyPredictModelWrapper
Some autoencoder thing, I'm not sure what this does.
getHeader() - Method in class hex.genmodel.GenModel
???
getInclusiveLevels() - Method in class hex.genmodel.algos.tree.SharedTreeNode
 
getInclusiveNa() - Method in class hex.genmodel.algos.tree.SharedTreeNode
 
getIntercept() - Method in class hex.genmodel.algos.glm.GlmMojoModel
 
getLeftChild() - Method in class hex.genmodel.algos.tree.SharedTreeNode
 
getModel() - Method in class hex.genmodel.easy.EasyPredictModelWrapper.Config
 
getModel(String) - Method in class hex.genmodel.MultiModelMojoReader
 
getModelCategories() - Method in class hex.genmodel.algos.glrm.GlrmMojoModel
 
getModelCategories() - Method in class hex.genmodel.GenModel
Override this for models that may produce results in different categories.
getModelCategories() - Method in interface hex.genmodel.IGenModel
For models with multiple categories, returns the set of all supported categories.
getModelCategory() - Method in class hex.genmodel.easy.EasyPredictModelWrapper
Get the category (type) of model.
getModelCategory() - Method in class hex.genmodel.GenModel
Returns this model category.
getModelCategory() - Method in interface hex.genmodel.IGenModel
Returns this model category.
getModelCategory() - Method in class hex.genmodel.MojoModel
 
getModelName() - Method in class hex.genmodel.algos.deeplearning.DeeplearningMojoReader
 
getModelName() - Method in class hex.genmodel.algos.deepwater.DeepwaterMojoReader
 
getModelName() - Method in class hex.genmodel.algos.drf.DrfMojoReader
 
getModelName() - Method in class hex.genmodel.algos.ensemble.StackedEnsembleMojoReader
 
getModelName() - Method in class hex.genmodel.algos.gbm.GbmMojoReader
 
getModelName() - Method in class hex.genmodel.algos.glm.GlmMojoReader
 
getModelName() - Method in class hex.genmodel.algos.glrm.GlrmMojoReader
 
getModelName() - Method in class hex.genmodel.algos.kmeans.KMeansMojoReader
 
getModelName() - Method in class hex.genmodel.algos.svm.SvmMojoReader
 
getModelName() - Method in class hex.genmodel.algos.word2vec.Word2VecMojoReader
 
getModelName() - Method in class hex.genmodel.ModelMojoReader
 
getMojoReader(String) - Method in class hex.genmodel.ModelMojoFactory
 
getName() - Method in class hex.genmodel.algos.tree.SharedTreeNode
 
getNames() - Method in class hex.genmodel.GenModel
The names of all columns used, including response and offset columns.
getNames() - Method in interface water.genmodel.IGeneratedModel
The names of columns used in the model.
getNodeNumber() - Method in class hex.genmodel.algos.tree.SharedTreeNode
 
getNumClasses(int) - Method in class hex.genmodel.GenModel
Get number of classes in the given column.
getNumClasses(int) - Method in interface water.genmodel.IGeneratedModel
Get number of classes in in given column.
getNumClusters() - Method in class hex.genmodel.algos.kmeans.KMeansMojoModel
 
getNumClusters() - Method in interface hex.genmodel.IClusteringModel
Returns number of cluster used by this model.
getNumCols() - Method in class hex.genmodel.GenModel
Returns number of columns used as input for training (i.e., exclude response and offset columns).
getNumCols() - Method in interface water.genmodel.IGeneratedModel
Returns number of columns used as input for training (i.e., exclude response and offset columns).
getNumResponseClasses() - Method in class hex.genmodel.GenModel
Return a number of classes in response column.
getNumResponseClasses() - Method in interface water.genmodel.IGeneratedModel
Return a number of classes in response column.
getParent() - Method in class hex.genmodel.algos.tree.SharedTreeNode
 
getPrediction(double[], double[], double[], double) - Static method in class hex.genmodel.GenModel
Utility function to get a best prediction from an array of class prediction distribution.
getPredsSize(ModelCategory) - Method in class hex.genmodel.algos.deeplearning.DeeplearningMojoModel
 
getPredsSize(ModelCategory) - Method in class hex.genmodel.algos.glrm.GlrmMojoModel
 
getPredsSize() - Method in class hex.genmodel.GenModel
Returns the expected size of preds array which is passed to `predict(double[], double[])` function.
getPredsSize(ModelCategory) - Method in class hex.genmodel.GenModel
 
getPredsSize() - Method in interface water.genmodel.IGeneratedModel
Returns the expected size of preds array which is passed to `predict(double[], float[])` function.
getPredValue() - Method in class hex.genmodel.algos.tree.SharedTreeNode
 
getResponseDomainValues() - Method in class hex.genmodel.easy.EasyPredictModelWrapper
Get the array of levels for the response column.
getResponseIdx() - Method in class hex.genmodel.GenModel
Returns the index of the response column inside getDomains().
getResponseIdx() - Method in interface water.genmodel.IGeneratedModel
Returns an index of the response column inside getDomains().
getResponseName() - Method in class hex.genmodel.GenModel
The name of the response column.
getResponseName() - Method in interface water.genmodel.IGeneratedModel
Deprecated.
getRightChild() - Method in class hex.genmodel.algos.tree.SharedTreeNode
 
getSplitValue() - Method in class hex.genmodel.algos.tree.SharedTreeNode
 
getSquaredError() - Method in class hex.genmodel.algos.tree.SharedTreeNode
 
getSubgraphNumber() - Method in class hex.genmodel.algos.tree.SharedTreeNode
 
getTextFile(String) - Method in class hex.genmodel.InMemoryMojoReaderBackend
 
getTextFile(String) - Method in interface hex.genmodel.MojoReaderBackend
 
getTotalUnknownCategoricalLevelsSeen() - Method in class hex.genmodel.easy.error.CountingErrorConsumer
Counts and returns all previously unseen categorical variables across all columns.
getUnknownCategoricalsPerColumn() - Method in class hex.genmodel.easy.error.CountingErrorConsumer
Returns a thread-safe Map with column names as keys and number of observed unknown categorical values associated with each column.
getUnknownLevel() - Method in exception hex.genmodel.easy.exception.PredictUnknownCategoricalLevelException
Get the unknown level which was not seen during model training.
getUseExtendedOutput() - Method in class hex.genmodel.easy.EasyPredictModelWrapper.Config
 
getUUID() - Method in class hex.genmodel.GenModel
 
getUUID() - Method in class hex.genmodel.MojoModel
 
getUUID() - Method in interface water.genmodel.IGeneratedModel
Returns model's unique identifier.
getVecSize() - Method in class hex.genmodel.algos.word2vec.Word2VecMojoModel
 
getVecSize() - Method in interface hex.genmodel.algos.word2vec.WordEmbeddingModel
Dimensionality of the vector space of this Word Embedding model
getWeight() - Method in class hex.genmodel.algos.tree.SharedTreeNode
 
GLM_identityInv(double) - Static method in class hex.genmodel.GenModel
 
GLM_inverseInv(double) - Static method in class hex.genmodel.GenModel
 
GLM_logInv(double) - Static method in class hex.genmodel.GenModel
 
GLM_logitInv(double) - Static method in class hex.genmodel.GenModel
 
GLM_ologitInv(double) - Static method in class hex.genmodel.GenModel
 
GLM_tweedieInv(double, double) - Static method in class hex.genmodel.GenModel
 
GlmMojoModel - Class in hex.genmodel.algos.glm
 
GlmMojoReader - Class in hex.genmodel.algos.glm
 
GlmMojoReader() - Constructor for class hex.genmodel.algos.glm.GlmMojoReader
 
GlmMultinomialMojoModel - Class in hex.genmodel.algos.glm
 
GlmOrdinalMojoModel - Class in hex.genmodel.algos.glm
 
GlrmInitialization - Enum in hex.genmodel.algos.glrm
Initialization strategy for matrices X and Y in the GLRM algorithm.
GlrmLoss - Enum in hex.genmodel.algos.glrm
Loss function for the GLRM algorithm.
GlrmMojoModel - Class in hex.genmodel.algos.glrm
 
GlrmMojoModel(String[], String[][], String) - Constructor for class hex.genmodel.algos.glrm.GlrmMojoModel
 
GlrmMojoReader - Class in hex.genmodel.algos.glrm
 
GlrmMojoReader() - Constructor for class hex.genmodel.algos.glrm.GlrmMojoReader
 
GlrmRegularizer - Enum in hex.genmodel.algos.glrm
Regularization method for matrices X and Y in the GLRM algorithm.
graph - Variable in class hex.genmodel.algos.deepwater.caffe.nano.Deepwater.Cmd
 

H

H2OPredictor - Class in water.util
Created by magnus on 5/5/16.
H2OPredictor(String, String) - Constructor for class water.util.H2OPredictor
 
hasRemaining() - Method in class hex.genmodel.utils.ByteBufferWrapper
 
hex - package hex
Shared code between the H2O runtime and generated POJO and POJO models.
hex.genmodel - package hex.genmodel
Low-level information about generated POJO and MOJO models.
hex.genmodel.algos.deeplearning - package hex.genmodel.algos.deeplearning
 
hex.genmodel.algos.deepwater - package hex.genmodel.algos.deepwater
 
hex.genmodel.algos.deepwater.caffe - package hex.genmodel.algos.deepwater.caffe
 
hex.genmodel.algos.deepwater.caffe.nano - package hex.genmodel.algos.deepwater.caffe.nano
 
hex.genmodel.algos.drf - package hex.genmodel.algos.drf
 
hex.genmodel.algos.ensemble - package hex.genmodel.algos.ensemble
 
hex.genmodel.algos.gbm - package hex.genmodel.algos.gbm
 
hex.genmodel.algos.glm - package hex.genmodel.algos.glm
 
hex.genmodel.algos.glrm - package hex.genmodel.algos.glrm
 
hex.genmodel.algos.kmeans - package hex.genmodel.algos.kmeans
 
hex.genmodel.algos.svm - package hex.genmodel.algos.svm
 
hex.genmodel.algos.tree - package hex.genmodel.algos.tree
 
hex.genmodel.algos.word2vec - package hex.genmodel.algos.word2vec
 
hex.genmodel.annotations - package hex.genmodel.annotations
 
hex.genmodel.easy - package hex.genmodel.easy
The easy prediction API for generated POJO and MOJO models.
hex.genmodel.easy.error - package hex.genmodel.easy.error
 
hex.genmodel.easy.exception - package hex.genmodel.easy.exception
Exceptions that can be raised by generated POJO and MOJO models.
hex.genmodel.easy.prediction - package hex.genmodel.easy.prediction
Prediction types that can be returned by generated POJO and MOJO models.
hex.genmodel.tools - package hex.genmodel.tools
Tools that use generated POJO and MOJO models.
hex.genmodel.utils - package hex.genmodel.utils
 

I

IClusteringModel - Interface in hex.genmodel
Clustering Model Interface
IGeneratedModel - Interface in water.genmodel
A generic interface to access generated models.
IGenModel - Interface in hex.genmodel
Interface publishing methods for generated models.
img2pixels(BufferedImage, int, int, int, float[], int, float[]) - Static method in class hex.genmodel.GenModel
 
impute(double) - Method in enum hex.genmodel.algos.glrm.GlrmLoss
\argmin_a L(u, a): Data imputation for real numeric values
init() - Method in class hex.genmodel.algos.deeplearning.DeeplearningMojoModel
 
InMemoryMojoReaderBackend - Class in hex.genmodel
 
InMemoryMojoReaderBackend(Map<String, byte[]>) - Constructor for class hex.genmodel.InMemoryMojoReaderBackend
 
inNames() - Method in class hex.genmodel.GenMunger
 
inputShape - Variable in class hex.genmodel.algos.deepwater.caffe.nano.Deepwater.Cmd
 
inputShape - Variable in class hex.genmodel.algos.deepwater.caffe.nano.Deepwater.Saved
 
INSTANCE - Static variable in class hex.genmodel.ModelMojoFactory
 
inTypes() - Method in class hex.genmodel.GenMunger
 
isAutoEncoder() - Method in class hex.genmodel.GenModel
Returns true if this model represents an AutoEncoder.
isAutoEncoder() - Method in interface water.genmodel.IGeneratedModel
 
isBoolColumn(String[]) - Static method in class hex.genmodel.utils.ArrayUtils
Check to see if a column is a boolean column.
isClassifier() - Method in class hex.genmodel.GenModel
Returns true if this model represents a classifier, else it is used for regression.
isClassifier() - Method in interface water.genmodel.IGeneratedModel
 
isForBinary() - Method in enum hex.genmodel.algos.glrm.GlrmLoss
 
isForCategorical() - Method in enum hex.genmodel.algos.glrm.GlrmLoss
 
isForNumeric() - Method in enum hex.genmodel.algos.glrm.GlrmLoss
 
isInclusiveNa() - Method in class hex.genmodel.algos.tree.SharedTreeNode
 
isInRange(int) - Method in class hex.genmodel.utils.GenmodelBitSet
 
isLeftward() - Method in class hex.genmodel.algos.tree.SharedTreeNode
 
isNaVsRest() - Method in class hex.genmodel.algos.tree.SharedTreeNode
 
isSupervised() - Method in class hex.genmodel.GenModel
Returns true for supervised models.
isSupervised() - Method in interface hex.genmodel.IGenModel
Returns true for supervised models.
isSupervised() - Method in class hex.genmodel.MojoModel
 

K

KMeans_closest(double[][], double[], String[][]) - Static method in class hex.genmodel.GenModel
 
KMeans_distance(double[], float[], int[], double[], double[]) - Static method in class hex.genmodel.GenModel
 
KMeans_distance(double[], double[], String[][]) - Static method in class hex.genmodel.GenModel
 
KMeans_distances(double[][], double[], String[][], double[]) - Static method in class hex.genmodel.GenModel
 
Kmeans_preprocessData(double[], double[], double[], int[]) - Static method in class hex.genmodel.GenModel
 
Kmeans_preprocessData(double, int, double[], double[], int[]) - Static method in class hex.genmodel.GenModel
 
KMeans_simplex(double[][], double[], String[][]) - Static method in class hex.genmodel.GenModel
 
KMeansMojoModel - Class in hex.genmodel.algos.kmeans
 
KMeansMojoReader - Class in hex.genmodel.algos.kmeans
 
KMeansMojoReader() - Constructor for class hex.genmodel.algos.kmeans.KMeansMojoReader
 

L

l2norm(double[]) - Static method in class hex.genmodel.utils.ArrayUtils
 
l2norm2(double[]) - Static method in class hex.genmodel.utils.ArrayUtils
 
l2norm2(double[], boolean) - Static method in class hex.genmodel.utils.ArrayUtils
 
label - Variable in class hex.genmodel.easy.prediction.BinomialModelPrediction
Label of the predicted level.
label - Variable in class hex.genmodel.easy.prediction.MultinomialModelPrediction
Label of the predicted level.
label - Variable in class hex.genmodel.easy.prediction.OrdinalModelPrediction
Label of the predicted level.
labelIndex - Variable in class hex.genmodel.easy.prediction.BinomialModelPrediction
0 or 1.
labelIndex - Variable in class hex.genmodel.easy.prediction.MultinomialModelPrediction
Index number of the predicted class (aka categorical or factor level) in the response column.
labelIndex - Variable in class hex.genmodel.easy.prediction.OrdinalModelPrediction
Index number of the predicted class (aka categorical or factor level) in the response column.
learningRate - Variable in class hex.genmodel.algos.deepwater.caffe.nano.Deepwater.Cmd
 
lgrad(double, double) - Method in enum hex.genmodel.algos.glrm.GlrmLoss
\grad_u L(u,a): Derivative of the numeric loss function with respect to u
LinearOut() - Constructor for class hex.genmodel.algos.deeplearning.ActivationUtils.LinearOut
 
link(double) - Method in enum hex.genmodel.utils.DistributionFamily
Canonical link
linkInv(double) - Method in enum hex.genmodel.utils.DistributionFamily
Canonical link inverse
linkInvString(String) - Method in enum hex.genmodel.utils.DistributionFamily
String version of link inverse (for POJO scoring code generation)
listAllLayers(BackendModel) - Method in class hex.genmodel.algos.deepwater.caffe.DeepwaterCaffeBackend
 
Load - Static variable in interface hex.genmodel.algos.deepwater.caffe.nano.Deepwater
 
load(String) - Static method in class hex.genmodel.MojoModel
Primary factory method for constructing MojoModel instances.
load(MojoReaderBackend) - Static method in class hex.genmodel.MojoModel
Advanced way of constructing Mojo models by supplying a custom mojoReader.
loadMeanImage(BackendModel, String) - Method in class hex.genmodel.algos.deepwater.caffe.DeepwaterCaffeBackend
 
loadParam(BackendModel, String) - Method in class hex.genmodel.algos.deepwater.caffe.DeepwaterCaffeBackend
 
loadParam(String) - Method in class hex.genmodel.algos.deepwater.caffe.DeepwaterCaffeModel
 
log(double) - Static method in enum hex.genmodel.utils.DistributionFamily
 
log_rescale(double[]) - Static method in class hex.genmodel.GenModel
 
loss(double, double) - Method in enum hex.genmodel.algos.glrm.GlrmLoss
Loss function for numeric variables

M

m - Variable in class hex.genmodel.easy.EasyPredictModelWrapper
 
main(String[]) - Static method in class hex.genmodel.tools.MungeCsv
CSV reader and predictor test program.
main(String[]) - Static method in class hex.genmodel.tools.PredictCsv
 
main(String[]) - Static method in class hex.genmodel.tools.PrintMojo
 
main(String[]) - Static method in class water.util.H2OPredictor
 
makeModel(String[], String[][], String) - Method in class hex.genmodel.algos.deeplearning.DeeplearningMojoReader
 
makeModel(String[], String[][], String) - Method in class hex.genmodel.algos.deepwater.DeepwaterMojoReader
 
makeModel(String[], String[][], String) - Method in class hex.genmodel.algos.drf.DrfMojoReader
 
makeModel(String[], String[][], String) - Method in class hex.genmodel.algos.ensemble.StackedEnsembleMojoReader
 
makeModel(String[], String[][], String) - Method in class hex.genmodel.algos.gbm.GbmMojoReader
 
makeModel(String[], String[][], String) - Method in class hex.genmodel.algos.glm.GlmMojoReader
 
makeModel(String[], String[][], String) - Method in class hex.genmodel.algos.glrm.GlrmMojoReader
 
makeModel(String[], String[][], String) - Method in class hex.genmodel.algos.kmeans.KMeansMojoReader
 
makeModel(String[], String[][], String) - Method in class hex.genmodel.algos.svm.SvmMojoReader
 
makeModel(String[], String[][], String) - Method in class hex.genmodel.algos.word2vec.Word2VecMojoReader
 
makeModel(String[], String[][], String) - Method in class hex.genmodel.ModelMojoReader
 
mapEnum(int, String) - Method in class hex.genmodel.GenModel
Maps given column's categorical to the integer used by this model (returns -1 if mapping not found).
mapEnum(int, String) - Method in interface water.genmodel.IGeneratedModel
Maps given column's categorical to integer used by this model.
MathUtils - Class in hex.genmodel.utils
Copied (partially) from water.util.MathUtils
MathUtils() - Constructor for class hex.genmodel.utils.MathUtils
 
maxArray(double[]) - Static method in class hex.genmodel.algos.deeplearning.ActivationUtils
 
maxIndex(double[], Random) - Static method in class hex.genmodel.utils.ArrayUtils
 
maxIndex(double[]) - Static method in class hex.genmodel.utils.ArrayUtils
 
MaxoutDropoutOut() - Constructor for class hex.genmodel.algos.deeplearning.ActivationUtils.MaxoutDropoutOut
 
MaxoutOut() - Constructor for class hex.genmodel.algos.deeplearning.ActivationUtils.MaxoutOut
 
mergeFrom(CodedInputByteBufferNano) - Method in class hex.genmodel.algos.deepwater.caffe.nano.Deepwater.Cmd
 
mergeFrom(CodedInputByteBufferNano) - Method in class hex.genmodel.algos.deepwater.caffe.nano.Deepwater.Saved
 
mimpute(double[]) - Method in enum hex.genmodel.algos.glrm.GlrmLoss
\argmin_a L(u, a): Data imputation for categorical values {0, 1, 2, ...}
minus(double, HashMap<String, String[]>) - Static method in class hex.genmodel.GenMunger
 
mlgrad(double[], int) - Method in enum hex.genmodel.algos.glrm.GlrmLoss
\grad_u L(u,a): Gradient of multidimensional loss function with respect to u
mlgrad(double[], int, double[], int) - Method in enum hex.genmodel.algos.glrm.GlrmLoss
\grad_u L(u,a): Gradient of multidimensional loss function with respect to u.
mloss(double[], int) - Method in enum hex.genmodel.algos.glrm.GlrmLoss
Loss function for categorical variables where the size of u represents the true column length.
mloss(double[], int, int) - Method in enum hex.genmodel.algos.glrm.GlrmLoss
Loss function for categorical variables performing same function as mloss above.
mod(double, HashMap<String, String[]>) - Static method in class hex.genmodel.GenMunger
 
ModelCategory - Enum in hex
Different prediction categories for models.
ModelMojoFactory - Class in hex.genmodel
Factory class for instantiating specific MojoGenmodel classes based on the algo name.
ModelMojoReader<M extends MojoModel> - Class in hex.genmodel
Helper class to deserialize a model from MOJO format.
ModelMojoReader() - Constructor for class hex.genmodel.ModelMojoReader
 
ModelPojo - Annotation Type in hex.genmodel.annotations
Annotation to simplify identification of model pojos.
ModelUtils - Class in water.util
Shared static code to support modeling, prediction, and scoring.
ModelUtils() - Constructor for class water.util.ModelUtils
 
modifyOutputs(double[], double[], double[]) - Method in class hex.genmodel.algos.deeplearning.DeeplearningMojoModel
 
MojoModel - Class in hex.genmodel
Prediction model based on the persisted binary data.
MojoModel(String[], String[][], String) - Constructor for class hex.genmodel.MojoModel
 
MojoReaderBackend - Interface in hex.genmodel
 
MojoReaderBackendFactory - Class in hex.genmodel
Factory class for vending MojoReaderBackend object that can be used to load MOJOs from different data sources.
MojoReaderBackendFactory() - Constructor for class hex.genmodel.MojoReaderBackendFactory
 
MojoReaderBackendFactory.CachingStrategy - Enum in hex.genmodel
 
momentum - Variable in class hex.genmodel.algos.deepwater.caffe.nano.Deepwater.Cmd
 
MultiModelMojoReader<M extends MojoModel> - Class in hex.genmodel
 
MultiModelMojoReader() - Constructor for class hex.genmodel.MultiModelMojoReader
 
MultinomialModelPrediction - Class in hex.genmodel.easy.prediction
Binomial classification model prediction.
MultinomialModelPrediction() - Constructor for class hex.genmodel.easy.prediction.MultinomialModelPrediction
 
multiply(double, HashMap<String, String[]>) - Static method in class hex.genmodel.GenMunger
 
MungeCsv - Class in hex.genmodel.tools
Simple driver program for reading a CSV file and munging it.
MungeCsv() - Constructor for class hex.genmodel.tools.MungeCsv
 

N

name - Variable in class hex.genmodel.algos.tree.SharedTreeSubgraph
 
name - Variable in class hex.genmodel.easy.prediction.SortedClassProbability
Name of this class level.
names() - Method in class hex.genmodel.GenMunger.Step
 
NaSplitDir - Enum in hex.genmodel.algos.tree
Copy of `hex.tree.DHistogram.NASplitDir` in package `h2o-algos`.
nchar(String, HashMap<String, String[]>) - Static method in class hex.genmodel.GenMunger
 
nclasses() - Method in class hex.genmodel.GenModel
Returns number of output classes for classifiers, 1 for regression models, and 0 for unsupervised models.
nclasses() - Method in interface hex.genmodel.IGenModel
Returns number of output classes for classifiers or 1 for regression models.
nclasses() - Method in class hex.genmodel.MojoModel
 
NeuralNetwork - Class in hex.genmodel.algos.deeplearning
 
NeuralNetwork(String, double, DeeplearningMojoModel.StoreWeightsBias, double[], int) - Constructor for class hex.genmodel.algos.deeplearning.NeuralNetwork
 
nfeatures() - Method in class hex.genmodel.GenModel
Returns number of input features.
nfeatures() - Method in interface hex.genmodel.IGenModel
Returns number of input features.
nfeatures() - Method in class hex.genmodel.MojoModel
 
nodesArray - Variable in class hex.genmodel.algos.tree.SharedTreeSubgraph
 

O

OrdinalModelPrediction - Class in hex.genmodel.easy.prediction
Ordinal classification model prediction.
OrdinalModelPrediction() - Constructor for class hex.genmodel.easy.prediction.OrdinalModelPrediction
 
original - Variable in class hex.genmodel.easy.prediction.AutoEncoderModelPrediction
Representation of the original input the way AutoEncoder model sees it (1-hot encoded categorical values)
outNames() - Method in class hex.genmodel.GenMunger
 
outNames() - Method in class hex.genmodel.GenMunger.Step
 

P

params() - Method in class hex.genmodel.GenMunger.Step
 
parseArrayOfDoubles(String) - Static method in class hex.genmodel.utils.ParseUtils
 
parseArrayOfInts(String) - Static method in class hex.genmodel.utils.ParseUtils
 
parseFrom(byte[]) - Static method in class hex.genmodel.algos.deepwater.caffe.nano.Deepwater.Cmd
 
parseFrom(CodedInputByteBufferNano) - Static method in class hex.genmodel.algos.deepwater.caffe.nano.Deepwater.Cmd
 
parseFrom(byte[]) - Static method in class hex.genmodel.algos.deepwater.caffe.nano.Deepwater.Saved
 
parseFrom(CodedInputByteBufferNano) - Static method in class hex.genmodel.algos.deepwater.caffe.nano.Deepwater.Saved
 
ParseUtils - Class in hex.genmodel.utils
Helper function for parsing the serialized model.
ParseUtils() - Constructor for class hex.genmodel.utils.ParseUtils
 
path - Variable in class hex.genmodel.algos.deepwater.caffe.nano.Deepwater.Cmd
 
position() - Method in class hex.genmodel.utils.ByteBufferWrapper
 
pow(double, HashMap<String, String[]>) - Static method in class hex.genmodel.GenMunger
 
preamble(ModelCategory, RowData) - Method in class hex.genmodel.easy.EasyPredictModelWrapper
 
preamble(ModelCategory, RowData, double) - Method in class hex.genmodel.easy.EasyPredictModelWrapper
 
pred(String) - Method in class water.util.H2OPredictor
 
predict(BackendModel, float[]) - Method in class hex.genmodel.algos.deepwater.caffe.DeepwaterCaffeBackend
 
predict(float[]) - Method in class hex.genmodel.algos.deepwater.caffe.DeepwaterCaffeModel
 
Predict - Static variable in interface hex.genmodel.algos.deepwater.caffe.nano.Deepwater
 
predict(RowData, ModelCategory) - Method in class hex.genmodel.easy.EasyPredictModelWrapper
Make a prediction on a new data point.
predict(RowData) - Method in class hex.genmodel.easy.EasyPredictModelWrapper
 
predict(RowData, double, double[]) - Method in class hex.genmodel.easy.EasyPredictModelWrapper
 
predict2(String, String) - Static method in class water.util.H2OPredictor
 
predict3(String, String, String) - Static method in class water.util.H2OPredictor
 
predictAutoEncoder(RowData) - Method in class hex.genmodel.easy.EasyPredictModelWrapper
Make a prediction on a new data point using an AutoEncoder model.
predictBinomial(RowData) - Method in class hex.genmodel.easy.EasyPredictModelWrapper
Make a prediction on a new data point using a Binomial model.
predictBinomial(RowData, double) - Method in class hex.genmodel.easy.EasyPredictModelWrapper
Make a prediction on a new data point using a Binomial model.
predictClustering(RowData) - Method in class hex.genmodel.easy.EasyPredictModelWrapper
Make a prediction on a new data point using a Clustering model.
PredictCsv - Class in hex.genmodel.tools
Simple driver program for reading a CSV file and making predictions.
PredictCsv() - Constructor for class hex.genmodel.tools.PredictCsv
 
predictDimReduction(RowData) - Method in class hex.genmodel.easy.EasyPredictModelWrapper
Make a prediction on a new data point using a Dimension Reduction model (PCA, GLRM)
PredictException - Exception in hex.genmodel.easy.exception
All generated model exceptions that can occur on the various predict methods derive from this.
PredictException(String) - Constructor for exception hex.genmodel.easy.exception.PredictException
 
predictMultinomial(RowData) - Method in class hex.genmodel.easy.EasyPredictModelWrapper
Make a prediction on a new data point using a Multinomial model.
PredictNumberFormatException - Exception in hex.genmodel.easy.exception
Unknown type exception.
PredictNumberFormatException(String) - Constructor for exception hex.genmodel.easy.exception.PredictNumberFormatException
 
predictOrdinal(RowData) - Method in class hex.genmodel.easy.EasyPredictModelWrapper
Make a prediction on a new data point using a Ordinal model.
predictRegression(RowData) - Method in class hex.genmodel.easy.EasyPredictModelWrapper
Make a prediction on a new data point using a Regression model.
PredictUnknownCategoricalLevelException - Exception in hex.genmodel.easy.exception
Unknown categorical level exception.
PredictUnknownCategoricalLevelException(String, String, String) - Constructor for exception hex.genmodel.easy.exception.PredictUnknownCategoricalLevelException
 
PredictUnknownTypeException - Exception in hex.genmodel.easy.exception
Unknown type exception.
PredictUnknownTypeException(String) - Constructor for exception hex.genmodel.easy.exception.PredictUnknownTypeException
 
predictWord2Vec(RowData) - Method in class hex.genmodel.easy.EasyPredictModelWrapper
Lookup word embeddings for a given word (or set of words).
PredictWrongModelCategoryException - Exception in hex.genmodel.easy.exception
Wrong model category exception.
PredictWrongModelCategoryException(String) - Constructor for exception hex.genmodel.easy.exception.PredictWrongModelCategoryException
 
print() - Method in class hex.genmodel.algos.tree.SharedTreeGraph
Debug printout of graph structure.
print() - Method in class hex.genmodel.algos.tree.SharedTreeNode
 
printDot(PrintStream, int, boolean, String) - Method in class hex.genmodel.algos.tree.SharedTreeGraph
Print graph output in a format readable by dot (graphviz).
PrintMojo - Class in hex.genmodel.tools
Print dot (graphviz) representation of one or more trees in a DRF or GBM model.
PrintMojo() - Constructor for class hex.genmodel.tools.PrintMojo
 
probability - Variable in class hex.genmodel.easy.prediction.SortedClassProbability
Prediction value for this class level.
project(double[], Random) - Method in enum hex.genmodel.algos.glrm.GlrmRegularizer
Project X,Y matrices into appropriate subspace so regularizer is finite.

R

randomSeed - Variable in class hex.genmodel.algos.deepwater.caffe.nano.Deepwater.Cmd
 
readblob(String) - Method in class hex.genmodel.ModelMojoReader
Retrieve binary data previously saved to the mojo file using `writeblob(key, blob)`.
readBytes(File) - Method in class hex.genmodel.algos.deepwater.caffe.DeepwaterCaffeBackend
 
readFrom(MojoReaderBackend) - Static method in class hex.genmodel.ModelMojoReader
 
readkv(String) - Method in class hex.genmodel.ModelMojoReader
Retrieve value from the model's kv store which was previously put there using `writekv(key, value)`.
readkv(String, T) - Method in class hex.genmodel.ModelMojoReader
Retrieves the value associated with a given key.
readModelData() - Method in class hex.genmodel.algos.deeplearning.DeeplearningMojoReader
 
readModelData() - Method in class hex.genmodel.algos.deepwater.DeepwaterMojoReader
 
readModelData() - Method in class hex.genmodel.algos.drf.DrfMojoReader
 
readModelData() - Method in class hex.genmodel.algos.gbm.GbmMojoReader
 
readModelData() - Method in class hex.genmodel.algos.glm.GlmMojoReader
 
readModelData() - Method in class hex.genmodel.algos.glrm.GlrmMojoReader
 
readModelData() - Method in class hex.genmodel.algos.kmeans.KMeansMojoReader
 
readModelData() - Method in class hex.genmodel.algos.svm.SvmMojoReader
 
readModelData() - Method in class hex.genmodel.algos.tree.SharedTreeMojoReader
 
readModelData() - Method in class hex.genmodel.algos.word2vec.Word2VecMojoReader
 
readModelData() - Method in class hex.genmodel.ModelMojoReader
 
readModelData() - Method in class hex.genmodel.MultiModelMojoReader
 
readParentModelData() - Method in class hex.genmodel.algos.ensemble.StackedEnsembleMojoReader
 
readParentModelData() - Method in class hex.genmodel.MultiModelMojoReader
 
readtext(String) - Method in class hex.genmodel.ModelMojoReader
Retrieve text previously saved using `startWritingTextFile` + `writeln` as an array of lines.
readtext(String, boolean) - Method in class hex.genmodel.ModelMojoReader
Retrieve text previously saved using `startWritingTextFile` + `writeln` as an array of lines.
reconstructed - Variable in class hex.genmodel.easy.prediction.AutoEncoderModelPrediction
Reconstructed data, the array has same length as the original input.
reconstructedRowData - Variable in class hex.genmodel.easy.prediction.AutoEncoderModelPrediction
Reconstructed data represented in RowData structure.
RectifierDropoutOut() - Constructor for class hex.genmodel.algos.deeplearning.ActivationUtils.RectifierDropoutOut
 
RectifierOut() - Constructor for class hex.genmodel.algos.deeplearning.ActivationUtils.RectifierOut
 
RegressionModelPrediction - Class in hex.genmodel.easy.prediction
Regression model prediction.
RegressionModelPrediction() - Constructor for class hex.genmodel.easy.prediction.RegressionModelPrediction
 
regularize(double[]) - Method in enum hex.genmodel.algos.glrm.GlrmRegularizer
Regularization function applied to a single row x_i or column y_j
regularize(double[][]) - Method in enum hex.genmodel.algos.glrm.GlrmRegularizer
Regularization applied to an entire matrix (sum over rows)
replaceall(String, HashMap<String, String[]>) - Static method in class hex.genmodel.GenMunger
 
rightChild - Variable in class hex.genmodel.algos.tree.SharedTreeNode
 
rootNode - Variable in class hex.genmodel.algos.tree.SharedTreeSubgraph
 
RowData - Class in hex.genmodel.easy
Column name to column value mapping for a new row (aka data point, observation, sample) to predict.
RowData() - Constructor for class hex.genmodel.easy.RowData
 
rproxgrad(double[], double, Random) - Method in enum hex.genmodel.algos.glrm.GlrmRegularizer
\prox_{\alpha_k*r}(u): Proximal gradient of (step size) * (regularization function) evaluated at vector u

S

sampleOOBRows(int, float, Random) - Static method in class water.util.ModelUtils
Sample out-of-bag rows with given rate with help of given sampler.
sampleOOBRows(int, float, Random, int[]) - Static method in class water.util.ModelUtils
Save - Static variable in interface hex.genmodel.algos.deepwater.caffe.nano.Deepwater
 
Saved() - Constructor for class hex.genmodel.algos.deepwater.caffe.nano.Deepwater.Saved
 
SaveGraph - Static variable in interface hex.genmodel.algos.deepwater.caffe.nano.Deepwater
 
saveModel(BackendModel, String) - Method in class hex.genmodel.algos.deepwater.caffe.DeepwaterCaffeBackend
 
saveModel(String) - Method in class hex.genmodel.algos.deepwater.caffe.DeepwaterCaffeModel
 
saveParam(BackendModel, String) - Method in class hex.genmodel.algos.deepwater.caffe.DeepwaterCaffeBackend
 
saveParam(String) - Method in class hex.genmodel.algos.deepwater.caffe.DeepwaterCaffeModel
 
scaleInPlace(double[], double[], double[]) - Static method in class hex.genmodel.GenMunger
 
score0(double[], double, double[]) - Method in class hex.genmodel.algos.deeplearning.DeeplearningMojoModel
This method will be derived from the scoring/prediction function of deeplearning model itself.
score0(double[], double[]) - Method in class hex.genmodel.algos.deeplearning.DeeplearningMojoModel
 
score0(double[], double, double[]) - Method in class hex.genmodel.algos.deepwater.DeepwaterMojoModel
Corresponds to `hex.DeepWater.score0()`
score0(double[], double[]) - Method in class hex.genmodel.algos.deepwater.DeepwaterMojoModel
 
score0(double[], double, double[]) - Method in class hex.genmodel.algos.drf.DrfMojoModel
Corresponds to `hex.tree.drf.DrfMojoModel.score0()`
score0(double[], double[]) - Method in class hex.genmodel.algos.drf.DrfMojoModel
 
score0(double[], double[]) - Method in class hex.genmodel.algos.ensemble.StackedEnsembleMojoModel
 
score0(double[], double, double[]) - Method in class hex.genmodel.algos.gbm.GbmMojoModel
Corresponds to `hex.tree.gbm.GbmMojoModel.score0()`
score0(double[], double[]) - Method in class hex.genmodel.algos.gbm.GbmMojoModel
 
score0(double[], double[]) - Method in class hex.genmodel.algos.glrm.GlrmMojoModel
This function corresponds to the DimReduction model category
score0(double[], double[]) - Method in class hex.genmodel.algos.kmeans.KMeansMojoModel
 
score0(double[], double[]) - Method in class hex.genmodel.algos.svm.SvmMojoModel
 
score0(double[], double[]) - Method in class hex.genmodel.algos.word2vec.Word2VecMojoModel
 
score0(double[], double[]) - Method in class hex.genmodel.GenModel
Subclasses implement the scoring logic.
score0(double[], double, double[]) - Method in class hex.genmodel.GenModel
 
score0(double[], double[]) - Method in interface hex.genmodel.IClusteringModel
 
scoreAllTrees(double[], double[]) - Method in class hex.genmodel.algos.tree.SharedTreeMojoModel
Score all trees and fill in the `preds` array.
scoreTree(byte[], double[], int, boolean, String[][]) - Static method in class hex.genmodel.algos.tree.SharedTreeMojoModel
Highly efficient (critical path) tree scoring Given a tree (in the form of a byte array) and the row of input data, compute either this tree's predicted value when `computeLeafAssignment` is false, or the the decision path within the tree (but no more than 64 levels) when `computeLeafAssignment` is true.
scoreTree0(byte[], double[], int, boolean) - Static method in class hex.genmodel.algos.tree.SharedTreeMojoModel
SET IN STONE FOR MOJO VERSION "1.00" - DO NOT CHANGE
scoreTree1(byte[], double[], int, boolean) - Static method in class hex.genmodel.algos.tree.SharedTreeMojoModel
SET IN STONE FOR MOJO VERSION "1.10" - DO NOT CHANGE
separator - Variable in class hex.genmodel.tools.PredictCsv
 
setCats(double[], double[], int[], int, int[], double[], double[], boolean) - Static method in class hex.genmodel.GenModel
 
setConvertInvalidNumbersToNa(boolean) - Method in class hex.genmodel.easy.EasyPredictModelWrapper.Config
Specify the default action when a string value cannot be converted to a number.
setConvertUnknownCategoricalLevelsToNa(boolean) - Method in class hex.genmodel.easy.EasyPredictModelWrapper.Config
Specify how to handle unknown categorical levels.
setErrorConsumer(EasyPredictModelWrapper.ErrorConsumer) - Method in class hex.genmodel.easy.EasyPredictModelWrapper.Config
Specify an instance of EasyPredictModelWrapper.ErrorConsumer the EasyPredictModelWrapper is going to call whenever an error defined by the EasyPredictModelWrapper.ErrorConsumer instance occurs.
setInput(double[], float[], int, int, int[], double[], double[], boolean, boolean) - Static method in class hex.genmodel.GenModel
 
setInput(double[], double[], double[], int[], int, int, int[], double[], double[], boolean, boolean) - Static method in class hex.genmodel.GenModel
 
setInvNumNA - Variable in class hex.genmodel.tools.PredictCsv
 
setModel(GenModel) - Method in class hex.genmodel.easy.EasyPredictModelWrapper.Config
Specify model object to wrap.
setParameter(BackendModel, String, float) - Method in class hex.genmodel.algos.deepwater.caffe.DeepwaterCaffeBackend
 
setParameters(int) - Method in enum hex.genmodel.algos.glrm.GlrmLoss
Initialize additional parameters on the loss function.
setUseExtendedOutput(boolean) - Method in class hex.genmodel.easy.EasyPredictModelWrapper.Config
Specify whether to include additional metadata in the prediction output.
SharedTreeGraph - Class in hex.genmodel.algos.tree
Graph for representing a GBM or DRF forest.
SharedTreeMojoModel - Class in hex.genmodel.algos.tree
Common ancestor for DrfMojoModel and GbmMojoModel.
SharedTreeMojoModel(String[], String[][], String) - Constructor for class hex.genmodel.algos.tree.SharedTreeMojoModel
 
SharedTreeMojoReader<M extends SharedTreeMojoModel> - Class in hex.genmodel.algos.tree
 
SharedTreeMojoReader() - Constructor for class hex.genmodel.algos.tree.SharedTreeMojoReader
 
SharedTreeNode - Class in hex.genmodel.algos.tree
Node in a tree.
SharedTreeSubgraph - Class in hex.genmodel.algos.tree
Subgraph for representing a tree.
sin(double, HashMap<String, String[]>) - Static method in class hex.genmodel.GenMunger
 
sizes - Variable in class hex.genmodel.algos.deepwater.caffe.nano.Deepwater.Cmd
 
skip(int) - Method in class hex.genmodel.utils.ByteBufferWrapper
Skip over some bytes in the byte buffer.
SoftmaxOut() - Constructor for class hex.genmodel.algos.deeplearning.ActivationUtils.SoftmaxOut
 
solver - Variable in class hex.genmodel.algos.deepwater.caffe.nano.Deepwater.Saved
 
solverType - Variable in class hex.genmodel.algos.deepwater.caffe.nano.Deepwater.Cmd
 
sort(int[], double[]) - Static method in class hex.genmodel.utils.ArrayUtils
Sort an integer array of indices based on values Updates indices in place, keeps values the same
sort(int[], double[], int) - Static method in class hex.genmodel.utils.ArrayUtils
 
sortByDescendingClassProbability(BinomialModelPrediction) - Method in class hex.genmodel.easy.EasyPredictModelWrapper
A helper function to return an array of binomial class probabilities for a prediction in sorted order.
SortedClassProbability - Class in hex.genmodel.easy.prediction
Class probability.
SortedClassProbability() - Constructor for class hex.genmodel.easy.prediction.SortedClassProbability
 
StackedEnsembleMojoModel - Class in hex.genmodel.algos.ensemble
 
StackedEnsembleMojoModel(String[], String[][], String) - Constructor for class hex.genmodel.algos.ensemble.StackedEnsembleMojoModel
 
StackedEnsembleMojoReader - Class in hex.genmodel.algos.ensemble
 
StackedEnsembleMojoReader() - Constructor for class hex.genmodel.algos.ensemble.StackedEnsembleMojoReader
 
Step(String[], String[], String[]) - Constructor for class hex.genmodel.GenMunger.Step
 
StringEscapeUtils - Class in hex.genmodel.utils
 
StringEscapeUtils() - Constructor for class hex.genmodel.utils.StringEscapeUtils
 
strsplit(String, HashMap<String, String[]>) - Static method in class hex.genmodel.GenMunger
 
subgraphArray - Variable in class hex.genmodel.algos.tree.SharedTreeGraph
 
subgraphNumber - Variable in class hex.genmodel.algos.tree.SharedTreeSubgraph
 
Success - Static variable in interface hex.genmodel.algos.deepwater.caffe.nano.Deepwater
 
SvmMojoModel - Class in hex.genmodel.algos.svm
 
SvmMojoReader - Class in hex.genmodel.algos.svm
 
SvmMojoReader() - Constructor for class hex.genmodel.algos.svm.SvmMojoReader
 

T

TanhDropoutOut() - Constructor for class hex.genmodel.algos.deeplearning.ActivationUtils.TanhDropoutOut
 
TanhOut() - Constructor for class hex.genmodel.algos.deeplearning.ActivationUtils.TanhOut
 
TmpMojoReaderBackend - Class in hex.genmodel
 
TmpMojoReaderBackend(File) - Constructor for class hex.genmodel.TmpMojoReaderBackend
 
toJson(BackendModel) - Method in class hex.genmodel.algos.deepwater.caffe.DeepwaterCaffeBackend
 
tolower(String, HashMap<String, String[]>) - Static method in class hex.genmodel.GenMunger
 
toupper(String, HashMap<String, String[]>) - Static method in class hex.genmodel.GenMunger
 
train(BackendModel, float[], float[]) - Method in class hex.genmodel.algos.deepwater.caffe.DeepwaterCaffeBackend
 
train(float[], float[]) - Method in class hex.genmodel.algos.deepwater.caffe.DeepwaterCaffeModel
 
Train - Static variable in interface hex.genmodel.algos.deepwater.caffe.nano.Deepwater
 
transform(RowData) - Method in class hex.genmodel.GenMunger.Step
 
transform0(String, float[]) - Method in class hex.genmodel.algos.word2vec.Word2VecMojoModel
 
transform0(String, float[]) - Method in interface hex.genmodel.algos.word2vec.WordEmbeddingModel
Transforms a given a word into a word vector
treeIndex(int, int) - Method in class hex.genmodel.algos.tree.SharedTreeMojoModel
 
trim(String, HashMap<String, String[]>) - Static method in class hex.genmodel.GenMunger
 
tryParse(String, Object) - Static method in class hex.genmodel.utils.ParseUtils
 
type - Variable in class hex.genmodel.algos.deepwater.caffe.nano.Deepwater.Cmd
 
types - Variable in class hex.genmodel.algos.deepwater.caffe.nano.Deepwater.Cmd
 
types() - Method in class hex.genmodel.GenMunger.Step
 

U

unescapeNewlines(String) - Static method in class hex.genmodel.utils.StringEscapeUtils
Inverse function to escapeNewlines
unknownLevel - Variable in exception hex.genmodel.easy.exception.PredictUnknownCategoricalLevelException
 
unseenCategorical(String, Object, String) - Method in class hex.genmodel.easy.EasyPredictModelWrapper.ErrorConsumer
Previously unseen categorical level has been detected
unseenCategorical(String, Object, String) - Method in class hex.genmodel.easy.error.CountingErrorConsumer
 
unseenCategorical(String, Object, String) - Method in class hex.genmodel.easy.error.VoidErrorConsumer
 
useGpu - Variable in class hex.genmodel.algos.deepwater.caffe.nano.Deepwater.Cmd
 

V

validateInputs(String, double, int, int, int, int) - Method in class hex.genmodel.algos.deeplearning.NeuralNetwork
 
value() - Method in enum hex.genmodel.algos.tree.NaSplitDir
 
value - Variable in class hex.genmodel.easy.prediction.RegressionModelPrediction
This value may be Double.NaN, which means NA (this will happen with GLM, for example, if one of the input values for a new data point is NA).
valueOf(String) - Static method in enum hex.genmodel.algos.glrm.GlrmInitialization
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum hex.genmodel.algos.glrm.GlrmLoss
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum hex.genmodel.algos.glrm.GlrmRegularizer
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum hex.genmodel.algos.tree.NaSplitDir
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum hex.genmodel.MojoReaderBackendFactory.CachingStrategy
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum hex.genmodel.utils.DistributionFamily
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum hex.ModelCategory
Returns the enum constant of this type with the specified name.
values() - Static method in enum hex.genmodel.algos.glrm.GlrmInitialization
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum hex.genmodel.algos.glrm.GlrmLoss
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum hex.genmodel.algos.glrm.GlrmRegularizer
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum hex.genmodel.algos.tree.NaSplitDir
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum hex.genmodel.MojoReaderBackendFactory.CachingStrategy
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum hex.genmodel.utils.DistributionFamily
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum hex.ModelCategory
Returns an array containing the constants of this enum type, in the order they are declared.
VoidErrorConsumer - Class in hex.genmodel.easy.error
A void implementation of EasyPredictModelWrapper.ErrorConsumer.
VoidErrorConsumer() - Constructor for class hex.genmodel.easy.error.VoidErrorConsumer
 

W

water.genmodel - package water.genmodel
Deprecated (see hex.genmodel instead).
water.util - package water.util
Deprecated (see hex.util instead).
Word2VecMojoModel - Class in hex.genmodel.algos.word2vec
 
Word2VecMojoReader - Class in hex.genmodel.algos.word2vec
 
Word2VecMojoReader() - Constructor for class hex.genmodel.algos.word2vec.Word2VecMojoReader
 
Word2VecPrediction - Class in hex.genmodel.easy.prediction
 
Word2VecPrediction() - Constructor for class hex.genmodel.easy.prediction.Word2VecPrediction
 
WordEmbeddingModel - Interface in hex.genmodel.algos.word2vec
Interface for models implementing Word Embeddings
wordEmbeddings - Variable in class hex.genmodel.easy.prediction.Word2VecPrediction
 
writeBytes(File, byte[]) - Method in class hex.genmodel.algos.deepwater.caffe.DeepwaterCaffeBackend
 
writeTo(CodedOutputByteBufferNano) - Method in class hex.genmodel.algos.deepwater.caffe.nano.Deepwater.Cmd
 
writeTo(CodedOutputByteBufferNano) - Method in class hex.genmodel.algos.deepwater.caffe.nano.Deepwater.Saved
 

_

_activation - Variable in class hex.genmodel.algos.deeplearning.DeeplearningMojoModel
 
_activation - Variable in class hex.genmodel.algos.deeplearning.NeuralNetwork
 
_all_drop_out_ratios - Variable in class hex.genmodel.algos.deeplearning.DeeplearningMojoModel
 
_allActivations - Variable in class hex.genmodel.algos.deeplearning.DeeplearningMojoModel
 
_archetypes - Variable in class hex.genmodel.algos.glrm.GlrmMojoModel
 
_balanceClasses - Variable in class hex.genmodel.MojoModel
 
_binomial_double_trees - Variable in class hex.genmodel.algos.drf.DrfMojoModel
 
_calib_glm_beta - Variable in class hex.genmodel.algos.tree.SharedTreeMojoModel
GLM's beta used for calibrating output probabilities using Platt Scaling.
_category - Variable in class hex.genmodel.MojoModel
 
_catNAFill - Variable in class hex.genmodel.algos.deeplearning.DeeplearningMojoModel
 
_catoffsets - Variable in class hex.genmodel.algos.deeplearning.DeeplearningMojoModel
 
_catOffsets - Variable in class hex.genmodel.algos.deepwater.DeepwaterMojoModel
 
_cats - Variable in class hex.genmodel.algos.deeplearning.DeeplearningMojoModel
 
_cats - Variable in class hex.genmodel.algos.deepwater.DeepwaterMojoModel
 
_catsA - Variable in class hex.genmodel.algos.deeplearning.DeeplearningMojoModel
 
_channels - Variable in class hex.genmodel.algos.deepwater.DeepwaterMojoModel
 
_compressed_trees - Variable in class hex.genmodel.algos.tree.SharedTreeMojoModel
Array of binary tree data, each tree being a byte[] array.
_compressed_trees_aux - Variable in class hex.genmodel.algos.tree.SharedTreeMojoModel
Array of auxiliary binary tree data, each being a byte[] array.
_computeGraph(int) - Method in class hex.genmodel.algos.tree.SharedTreeMojoModel
Compute a graph of the forest.
_defaultThreshold - Variable in class hex.genmodel.MojoModel
 
_domains - Variable in class hex.genmodel.GenModel
Categorical (factor/enum) mappings, per column.
_family - Variable in class hex.genmodel.algos.deeplearning.DeeplearningMojoModel
 
_family - Variable in class hex.genmodel.algos.gbm.GbmMojoModel
 
_gammax - Variable in class hex.genmodel.algos.glrm.GlrmMojoModel
 
_height - Variable in class hex.genmodel.algos.deepwater.DeepwaterMojoModel
 
_imputeMeans - Variable in class hex.genmodel.algos.deeplearning.DeeplearningMojoModel
 
_init - Variable in class hex.genmodel.algos.glrm.GlrmMojoModel
 
_init_f - Variable in class hex.genmodel.algos.gbm.GbmMojoModel
 
_inputs - Variable in class hex.genmodel.algos.deeplearning.NeuralNetwork
 
_inSize - Variable in class hex.genmodel.algos.deeplearning.NeuralNetwork
 
_losses - Variable in class hex.genmodel.algos.glrm.GlrmMojoModel
 
_maxK - Variable in class hex.genmodel.algos.deeplearning.NeuralNetwork
 
_meanImageData - Variable in class hex.genmodel.algos.deepwater.DeepwaterMojoModel
 
_mini_batch_size - Variable in class hex.genmodel.algos.deeplearning.DeeplearningMojoModel
 
_mini_batch_size - Variable in class hex.genmodel.algos.deepwater.DeepwaterMojoModel
 
_model - Variable in class hex.genmodel.ModelMojoReader
 
_modelClassDistrib - Variable in class hex.genmodel.MojoModel
 
_mojo_version - Variable in class hex.genmodel.algos.tree.SharedTreeMojoModel
 
_names - Variable in class hex.genmodel.GenModel
Column names; last is response for supervised models
_ncats - Variable in class hex.genmodel.algos.glrm.GlrmMojoModel
 
_nclasses - Variable in class hex.genmodel.MojoModel
 
_ncolA - Variable in class hex.genmodel.algos.glrm.GlrmMojoModel
 
_ncolX - Variable in class hex.genmodel.algos.glrm.GlrmMojoModel
 
_ncolY - Variable in class hex.genmodel.algos.glrm.GlrmMojoModel
 
_nfeatures - Variable in class hex.genmodel.MojoModel
 
_nnums - Variable in class hex.genmodel.algos.glrm.GlrmMojoModel
 
_normmul - Variable in class hex.genmodel.algos.deeplearning.DeeplearningMojoModel
 
_normMul - Variable in class hex.genmodel.algos.deepwater.DeepwaterMojoModel
 
_normMul - Variable in class hex.genmodel.algos.glrm.GlrmMojoModel
 
_normrespmul - Variable in class hex.genmodel.algos.deeplearning.DeeplearningMojoModel
 
_normRespMul - Variable in class hex.genmodel.algos.deepwater.DeepwaterMojoModel
 
_normrespsub - Variable in class hex.genmodel.algos.deeplearning.DeeplearningMojoModel
 
_normRespSub - Variable in class hex.genmodel.algos.deepwater.DeepwaterMojoModel
 
_normsub - Variable in class hex.genmodel.algos.deeplearning.DeeplearningMojoModel
 
_normSub - Variable in class hex.genmodel.algos.deepwater.DeepwaterMojoModel
 
_normSub - Variable in class hex.genmodel.algos.glrm.GlrmMojoModel
 
_nrowY - Variable in class hex.genmodel.algos.glrm.GlrmMojoModel
 
_ntree_groups - Variable in class hex.genmodel.algos.tree.SharedTreeMojoModel
_ntree_groups is the number of trees requested by the user.
_ntrees_per_group - Variable in class hex.genmodel.algos.tree.SharedTreeMojoModel
 
_numLayers - Variable in class hex.genmodel.algos.deeplearning.DeeplearningMojoModel
 
_numLevels - Variable in class hex.genmodel.algos.glrm.GlrmMojoModel
 
_nums - Variable in class hex.genmodel.algos.deeplearning.DeeplearningMojoModel
 
_nums - Variable in class hex.genmodel.algos.deepwater.DeepwaterMojoModel
 
_numsA - Variable in class hex.genmodel.algos.deeplearning.DeeplearningMojoModel
 
_offsetColumn - Variable in class hex.genmodel.GenModel
Name of the column with offsets (used for certain types of models).
_outputs - Variable in class hex.genmodel.algos.deeplearning.NeuralNetwork
 
_outSize - Variable in class hex.genmodel.algos.deeplearning.NeuralNetwork
 
_params - Variable in class hex.genmodel.GenMunger.Step
 
_permutation - Variable in class hex.genmodel.algos.glrm.GlrmMojoModel
 
_priorClassDistrib - Variable in class hex.genmodel.MojoModel
 
_problem_type - Variable in class hex.genmodel.algos.deepwater.DeepwaterMojoModel
 
_reader - Variable in class hex.genmodel.ModelMojoReader
 
_regx - Variable in class hex.genmodel.algos.glrm.GlrmMojoModel
 
_responseColumn - Variable in class hex.genmodel.GenModel
Name of the response column used for training (only for supervised models).
_steps - Variable in class hex.genmodel.GenMunger
 
_supervised - Variable in class hex.genmodel.MojoModel
 
_units - Variable in class hex.genmodel.algos.deeplearning.DeeplearningMojoModel
 
_use_all_factor_levels - Variable in class hex.genmodel.algos.deeplearning.DeeplearningMojoModel
 
_useAllFactorLevels - Variable in class hex.genmodel.algos.deepwater.DeepwaterMojoModel
 
_uuid - Variable in class hex.genmodel.MojoModel
 
_weightsAndBias - Variable in class hex.genmodel.algos.deeplearning.DeeplearningMojoModel
 
_weightsAndBias - Variable in class hex.genmodel.algos.deeplearning.NeuralNetwork
 
_width - Variable in class hex.genmodel.algos.deepwater.DeepwaterMojoModel
 
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