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

A

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 the neurons in the hidden layers.
actual_best_model_key - Variable in class hex.deeplearning.DeepLearningModel
 
actual_train_samples_per_iteration - Variable in class hex.deeplearning.DeepLearningModel
 
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.
add(DeepLearningModel.DeepLearningModelInfo) - Method in class hex.deeplearning.DeepLearningModel.DeepLearningModelInfo
 
add(int, int, float) - Method in class hex.deeplearning.Neurons.DenseColMatrix
 
add(int, int, float) - Method in class hex.deeplearning.Neurons.DenseRowMatrix
 
add(int, float) - Method in class hex.deeplearning.Neurons.DenseVector
 
add(int, int, float) - Method in interface hex.deeplearning.Neurons.Matrix
 
add(int, int, float) - Method in class hex.deeplearning.Neurons.SparseRowMatrix
 
add(int, float) - Method in class hex.deeplearning.Neurons.SparseVector
 
add(int, float) - Method in interface hex.deeplearning.Neurons.Vector
 
add(double, double, double, double) - Method in class hex.glm.GLMValidation
 
add(Gram) - Method in class hex.gram.Gram
 
add(Word2VecModel.Word2VecModelInfo) - Method in class hex.word2vec.Word2VecModel.Word2VecModelInfo
Used to add together the weight vectors between two map instances.
add_processed_global(long) - Method in class hex.deeplearning.DeepLearningModel.DeepLearningModelInfo
 
add_processed_local(long) - Method in class hex.deeplearning.DeepLearningModel.DeepLearningModelInfo
 
addBinId(int) - Method in class hex.DataInfo.Row
 
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
 
addGloballyProcessed(long) - Method in class hex.word2vec.Word2VecModel.Word2VecModelInfo
 
addKTrees(DTree[]) - Method in class hex.tree.SharedTreeModel.SharedTreeOutput
 
addLocallyProcessed(long) - Method in class hex.word2vec.Word2VecModel.Word2VecModelInfo
 
addNum(int, double) - Method in class hex.DataInfo.Row
 
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
 
adjustGradient(double[], double[]) - Method in class hex.glm.GLM.BetaConstraint
 
adjustToNewLambda(double, double, double, boolean) - Method in class hex.glm.GLM.GLMTaskInfo
 
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.L1Solver(double, int) - Constructor for class hex.optimization.ADMM.L1Solver
 
ADMM.L1Solver(double, int, double, double) - Constructor for class hex.optimization.ADMM.L1Solver
 
ADMM.ProximalSolver - Interface in hex.optimization
 
alpha - Variable in class hex.schemas.GLMV3.GLMParametersV3
 
append(T) - Method in class hex.tree.drf.TreeMeasuresCollector.TreeMeasures
 
append(TreeMeasuresCollector.TreeSSE) - Method in class hex.tree.drf.TreeMeasuresCollector.TreeSSE
 
append(float, long) - Method in class hex.tree.drf.TreeMeasuresCollector.TreeSSE
Append a tree sse to a list of trees.
append(long, long) - 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
 
applyHypers(KMeansModel.KMeansParameters, double[]) - Method in class hex.kmeans.KMeansGrid
 
applyHypers(DRFModel.DRFParameters, double[]) - Method in class hex.tree.drf.DRFGrid
 
applyHypers(GBMModel.GBMParameters, double[]) - Method in class hex.tree.gbm.GBMGrid
 
applyHypers(P, double[]) - Method in class hex.tree.SharedTreeGrid
 
apriori - Variable in class hex.schemas.NaiveBayesModelV3.NaiveBayesModelOutputV3
 
archetypes - Variable in class hex.schemas.GLRMModelV3.GLRMModelOutputV3
 
asSSE(TreeMeasuresCollector.TreeMeasures) - Static method in class hex.tree.drf.TreeMeasuresCollector
 
asVotes(TreeMeasuresCollector.TreeMeasures) - Static method in class hex.tree.drf.TreeMeasuresCollector
 
autoencoder - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
 
autoEncoderError(int) - Method in class hex.deeplearning.Neurons
Helper to compute the reconstruction error for auto-encoders (part of the gradient computation)
average_activation - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
 
avg_change_obj - Variable in class hex.schemas.GLRMModelV3.GLRMModelOutputV3
 

B

bad - Variable in class hex.DataInfo.Row
 
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.GLMV3.GLMParametersV3
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.
begin() - Method in class hex.deeplearning.Neurons.SparseVector
 
bestCol(DTree.UndecidedNode, DHistogram[]) - Method in class hex.tree.DTree.DecidedNode
 
bestSubmodel() - Method in class hex.glm.GLMModel.GLMOutput
 
beta() - Method in class hex.glm.GLMModel
 
beta() - Method in class hex.glm.GLMModel.GLMOutput
 
beta - Variable in class hex.glm.GLMModel.Submodel
 
beta - Variable in class hex.schemas.MakeGLMModelV3
 
beta_constraints - Variable in class hex.schemas.GLMV3.GLMParametersV3
 
beta_epsilon - Variable in class hex.schemas.GLMV3.GLMParametersV3
 
bin() - Method in class hex.tree.DTree.Split
 
binIds - Variable in class hex.DataInfo.Row
 
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
 
bins(int) - Method in class hex.tree.DHistogram
 
bits() - Method in class hex.deeplearning.Dropout
 
bprop() - Method in class hex.deeplearning.Neurons
Back propagation
bprop() - Method in class hex.deeplearning.Neurons.Input
 
bprop(float) - Method in class hex.deeplearning.Neurons.Linear
Backpropagation for regression
bprop() - Method in class hex.deeplearning.Neurons.Maxout
 
bprop() - Method in class hex.deeplearning.Neurons.Output
 
bprop() - Method in class hex.deeplearning.Neurons.Rectifier
 
bprop(int) - Method in class hex.deeplearning.Neurons.Softmax
Backpropagation for classification Update every weight as follows: w += -rate * dE/dw Compute dE/dw via chain rule: dE/dw = dE/dy * dy/dnet * dnet/dw, where net = sum(xi*wi)+b and y = activation function
bprop() - Method in class hex.deeplearning.Neurons.Tanh
 
build_tree_one_node - Variable in class hex.schemas.DRFV3.DRFParametersV3
 
builderVisibility() - Method in class hex.coxph.CoxPH
 
builderVisibility() - Method in class hex.deeplearning.DeepLearning
 
builderVisibility() - Method in class hex.example.Example
 
builderVisibility() - Method in class hex.glm.GLM
 
builderVisibility() - Method in class hex.glrm.GLRM
 
builderVisibility() - Method in class hex.grep.Grep
 
builderVisibility() - Method in class hex.kmeans.KMeans
 
builderVisibility() - Method in class hex.naivebayes.NaiveBayes
 
builderVisibility() - Method in class hex.pca.PCA
 
builderVisibility() - Method in class hex.svd.SVD
 
builderVisibility() - Method in class hex.tree.drf.DRF
 
builderVisibility() - Method in class hex.tree.gbm.GBM
 
builderVisibility() - Method in class hex.word2vec.Word2Vec
 
buildLayer(Frame, int, int, DTree[], int[], DHistogram[][][], boolean, boolean) - Method in class hex.tree.SharedTree
 
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.tree.SharedTree.Driver
 
buildModelOutput() - Method in class hex.word2vec.Word2VecModel
 
byteSize() - Method in class hex.tree.DHistogram
 
byteSize0() - Method in class hex.tree.DBinomHistogram
 
byteSize0() - Method in class hex.tree.DHistogram
 
byteSize0() - Method in class hex.tree.DRealHistogram
 

C

c1 - Static variable in class hex.optimization.L_BFGS
 
calcCounts(CoxPHModel, CoxPH.CoxPHTask) - Method in class hex.coxph.CoxPH.CoxPHDriver
 
calcCumhaz_0(CoxPHModel, CoxPH.CoxPHTask) - Method in class hex.coxph.CoxPH.CoxPHDriver
 
calcLoglik(CoxPHModel, CoxPH.CoxPHTask) - Method in class hex.coxph.CoxPH.CoxPHDriver
 
calcModelStats(CoxPHModel, double[], double) - Method in class hex.coxph.CoxPH.CoxPHDriver
 
calcOutlierThreshold(Vec, double) - Method in class hex.deeplearning.DeepLearningModel
Compute quantile-based threshold (in reconstruction error) to find outliers
can_build() - Method in class hex.coxph.CoxPH
 
can_build() - Method in class hex.deeplearning.DeepLearning
 
can_build() - Method in class hex.example.Example
 
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.kmeans.KMeans
 
can_build() - Method in class hex.naivebayes.NaiveBayes
 
can_build() - Method in class hex.pca.PCA
 
can_build() - Method in class hex.svd.SVD
 
can_build() - Method in class hex.tree.drf.DRF
 
can_build() - Method in class hex.tree.gbm.GBM
 
can_build() - Method in class hex.word2vec.Word2Vec
 
canonical() - Method in class hex.glm.GLMModel.GLMParameters
 
centers - Variable in class hex.schemas.KMeansModelV3.KMeansModelOutputV3
 
centers_std - Variable in class hex.schemas.KMeansModelV3.KMeansModelOutputV3
 
checkKKTsAndComplete(boolean) - Method in class hex.glm.GLM.GLMSingleLambdaTsk
 
checkMemoryFootPrint() - Method in class hex.deeplearning.DeepLearning
 
checkMemoryFootPrint() - Method in class hex.glm.GLM
 
checkMemoryFootPrint(DataInfo) - Method in class hex.glm.GLM
 
checkMemoryFootPrint() - Method in class hex.kmeans.KMeans
 
checkMemoryFootPrint() - Method in class hex.naivebayes.NaiveBayes
 
checkMemoryFootPrint() - Method in class hex.pca.PCA
 
checkMemoryFootPrint() - Method in class hex.tree.SharedTree
 
checkpoint - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
A model key associated with a previously trained Deep Learning model.
checksum_impl() - Method in class hex.DataInfo
 
checksum_impl() - Method in class hex.deeplearning.DeepLearningModel
 
checksum_impl() - Method in class hex.deeplearning.DeepLearningModel.DeepLearningModelInfo
 
checksum_impl() - Method in class hex.glm.GLMModel
 
checksum_impl() - Method in class hex.tree.CompressedTree
 
chk_nids(Chunk[], int) - Method in class hex.tree.SharedTree
 
chk_oobt(Chunk[]) - Method in class hex.tree.DTreeScorer
 
chk_oobt(Chunk[]) - Method in class hex.tree.SharedTree
 
chk_resp(Chunk[]) - Method in class hex.tree.DTreeScorer
 
chk_resp(Chunk[]) - Method in class hex.tree.SharedTree
 
chk_tree(Chunk[], int) - Method in class hex.tree.DTreeScorer
 
chk_tree(Chunk[], int) - Method in class hex.tree.SharedTree
 
chk_u(Chunk[], int, int) - Static method in class hex.svd.SVD
 
chk_work(Chunk[], int) - Method in class hex.tree.SharedTree
 
chk_xnew(Chunk[], int, int, int) - Static method in class hex.glrm.GLRM
 
chk_xold(Chunk[], int, int) - Static method in class hex.glrm.GLRM
 
cholesky(Gram.Cholesky) - Method in class hex.gram.Gram
 
cholesky(Gram.Cholesky, boolean, String) - Method in class hex.gram.Gram
Compute the Cholesky decomposition.
chunkDone(long) - Method in class hex.deeplearning.DeepLearningTask
 
chunkDone(long) - Method in class hex.FrameTask
Override this to do post-chunk processing work.
chunkDone(long) - Method in class hex.gram.Gram.GramTask
 
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.gram.Gram.GramTask
 
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.GLMV3.GLMParametersV3
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 - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningScoring
 
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.glm.GLMModel.GLMOutput
 
closeLocal() - Method in class hex.FrameTask
 
closeLocal() - Method in class hex.word2vec.WordVectorTrainer
 
cm() - Method in class hex.deeplearning.DeepLearningModel
 
cnt - Variable in class hex.schemas.SynonymV3
 
coefficientNames() - Method in class hex.glm.GLMModel.GLMOutput
 
coefficients() - Method in class hex.glm.GLMModel
get beta coefficients in a map indexed by name
coefNames() - 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
 
collectSSE(CompressedTree[], int, Frame, int, float, int, double) - Static method in class hex.tree.drf.TreeMeasuresCollector
 
collectVotes(CompressedTree[], int, Frame, int, float, int, double) - Static method in class hex.tree.drf.TreeMeasuresCollector
 
cols() - Method in class hex.deeplearning.Neurons.DenseColMatrix
 
cols() - Method in class hex.deeplearning.Neurons.DenseRowMatrix
 
cols() - Method in interface hex.deeplearning.Neurons.Matrix
 
cols() - Method in class hex.deeplearning.Neurons.SparseRowMatrix
 
compareTo(DeepLearningModel) - Method in class hex.deeplearning.DeepLearningModel
 
compareTo(ValueString) - Method in class hex.word2vec.WordCountTask.ValueStringCount
 
compress(int, int) - Method in class hex.tree.DTree
 
compress(AutoBuffer) - Method in class hex.tree.DTree.DecidedNode
 
compress(AutoBuffer) - Method in class hex.tree.DTree.Node
 
compress(AutoBuffer) - Method in class hex.tree.DTree.UndecidedNode
 
CompressedTree - Class in hex.tree
 
CompressedTree(byte[], int, long, int, int) - Constructor for class hex.tree.CompressedTree
 
compute() - Method in class hex.gram.Gram.Cholesky.ParSolver
 
compute2() - Method in class hex.coxph.CoxPH.CoxPHDriver
 
compute2() - Method in class hex.deeplearning.DeepLearning.DeepLearningDriver
 
compute2() - Method in class hex.glm.GLM.GLMDriver
 
compute2() - Method in class hex.glm.GLM.GLMSingleLambdaTsk
 
compute2() - Method in class hex.tree.SharedTree.Driver
 
compute_metrics - Variable in class hex.schemas.NaiveBayesV3.NaiveBayesParametersV3
 
computeAIC() - Method in class hex.glm.GLMValidation
 
computeAUC() - Method in class hex.glm.GLMValidation
 
computePriorClassDistribution() - Method in class hex.tree.SharedTree
 
computeStats() - Method in class hex.deeplearning.DeepLearningModel.DeepLearningModelInfo
 
computeVariableImportances() - Method in class hex.deeplearning.DeepLearningModel.DeepLearningModelInfo
Compute Variable Importance, based on GEDEON: DATA MINING OF INPUTS: ANALYSING MAGNITUDE AND FUNCTIONAL MEASURES
converged - Variable in class hex.optimization.L_BFGS.Result
 
copyOver(WordCountTask) - Method in class hex.word2vec.WordCountTask
 
cos_sim - Variable in class hex.schemas.SynonymV3
 
cosineSimilarity(float[], float[]) - Method in class hex.word2vec.Word2VecModel
Basic calculation of cosine similarity
countEvents - Variable in class hex.coxph.CoxPH.CoxPHTask
 
CoxPH - Class in hex.coxph
Deep Learning Neural Net implementation based on MRTask
CoxPH(CoxPHModel.CoxPHParameters) - Constructor for class hex.coxph.CoxPH
 
CoxPH.CoxPHDriver - Class in hex.coxph
 
CoxPH.CoxPHDriver() - Constructor for class hex.coxph.CoxPH.CoxPHDriver
 
CoxPH.CoxPHTask - Class in hex.coxph
 
CoxPHBuilderHandler - Class in hex.api
 
CoxPHBuilderHandler() - Constructor for class hex.api.CoxPHBuilderHandler
 
CoxPHModel - Class in hex.coxph
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
CoxPHModel(Key, CoxPHModel.CoxPHParameters, CoxPHModel.CoxPHOutput) - Constructor for class hex.coxph.CoxPHModel
 
CoxPHModel.CoxPHOutput - Class in hex.coxph
 
CoxPHModel.CoxPHOutput(CoxPH) - Constructor for class hex.coxph.CoxPHModel.CoxPHOutput
 
CoxPHModel.CoxPHParameters - Class in hex.coxph
 
CoxPHModel.CoxPHParameters() - Constructor for class hex.coxph.CoxPHModel.CoxPHParameters
 
CoxPHModel.CoxPHParameters.CoxPHTies - Enum in hex.coxph
 
CoxPHModelV3 - Class in hex.schemas
 
CoxPHModelV3() - Constructor for class hex.schemas.CoxPHModelV3
 
CoxPHModelV3.CoxPHModelOutputV3 - Class in hex.schemas
 
CoxPHModelV3.CoxPHModelOutputV3() - Constructor for class hex.schemas.CoxPHModelV3.CoxPHModelOutputV3
 
CoxPHV3 - Class in hex.schemas
 
CoxPHV3() - Constructor for class hex.schemas.CoxPHV3
 
CoxPHV3.CoxPHParametersV3 - Class in hex.schemas
 
CoxPHV3.CoxPHParametersV3() - Constructor for class hex.schemas.CoxPHV3.CoxPHParametersV3
 
createBuilder(KMeansModel.KMeansParameters) - Method in class hex.kmeans.KMeansGrid
 
createBuilder(DRFModel.DRFParameters) - Method in class hex.tree.drf.DRFGrid
 
createBuilder(GBMModel.GBMParameters) - Method in class hex.tree.gbm.GBMGrid
 
createCenterTable(KMeansModel.KMeansOutput, boolean) - Static method in class hex.kmeans.KMeans
 
createGrid(Frame) - Method in class hex.api.DRFGridSearchHandler
 
createGrid(Frame) - Method in class hex.api.GBMGridSearchHandler
 
createGrid(Frame) - Method in class hex.api.KMeansGridSearchHandler
 
createGrid(Frame) - Method in class hex.GridSearchHandler
 
createImpl() - Method in class hex.schemas.CoxPHModelV3
 
createImpl() - Method in class hex.schemas.CoxPHV3.CoxPHParametersV3
 
createImpl() - Method in class hex.schemas.DeepLearningModelV3
 
createImpl() - Method in class hex.schemas.DRFModelV3
 
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.KMeansModelV3
 
createImpl() - Method in class hex.schemas.NaiveBayesModelV3
 
createImpl() - Method in class hex.schemas.PCAModelV3
 
createImpl() - Method in class hex.schemas.SVDModelV3
 
createImpl() - Method in class hex.schemas.Word2VecModelV3
 
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.ExampleModelV3
 
createOutputSchema() - Method in class hex.schemas.GBMModelV3
 
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.KMeansModelV3
 
createOutputSchema() - Method in class hex.schemas.NaiveBayesModelV3
 
createOutputSchema() - Method in class hex.schemas.PCAModelV3
 
createOutputSchema() - Method in class hex.schemas.SVDModelV3
 
createOutputSchema() - Method in class hex.schemas.Word2VecModelV3
 
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.ExampleModelV3
 
createParametersSchema() - Method in class hex.schemas.GBMModelV3
 
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.KMeansModelV3
 
createParametersSchema() - Method in class hex.schemas.NaiveBayesModelV3
 
createParametersSchema() - Method in class hex.schemas.PCAModelV3
 
createParametersSchema() - Method in class hex.schemas.SVDModelV3
 
createParametersSchema() - Method in class hex.schemas.Word2VecModelV3
 
createProgressKey() - Method in class hex.pca.PCA.EmbeddedSVD
 
createRNG(long) - Static method in class hex.tree.SharedTree
 
createSummaryTable() - Method in class hex.deeplearning.DeepLearningModel.DeepLearningModelInfo
 
ctree(int, int) - Method in class hex.tree.SharedTreeModel.SharedTreeOutput
 

D

d - Variable in class hex.schemas.SVDModelV3.SVDModelOutputV3
 
data_info() - Method in class hex.deeplearning.DeepLearningModel.DeepLearningModelInfo
 
data_row(Chunk[], int, double[]) - Method in class hex.tree.SharedTree
 
DataInfo - Class in hex
Created by tomasnykodym on 1/29/15.
DataInfo(Key, Frame, Frame, int, boolean, DataInfo.TransformType, DataInfo.TransformType, boolean, boolean, boolean, boolean) - Constructor for class hex.DataInfo
 
DataInfo.Row - Class in hex
 
DataInfo.Row(boolean, int, int, int, double) - Constructor for class hex.DataInfo.Row
 
DataInfo.TransformType - Enum in hex
 
DBinomHistogram - Class in hex.tree
A Histogram, computed in parallel over a Vec.
DBinomHistogram(String, int, int, byte, float, float, long) - Constructor for class hex.tree.DBinomHistogram
 
decided(int) - Method in class hex.tree.DTree
 
DECIDED_ROW - Static variable in class hex.tree.ScoreBuildHistogram
Marker for already decided row.
decompose_2(double[][], int, int) - Static method in class hex.gram.Gram.InPlaceCholesky
 
deep_clone() - Method in class hex.DataInfo
 
DeepLearning - Class in hex.deeplearning
Deep Learning Neural Net implementation based on MRTask
DeepLearning(DeepLearningModel.DeepLearningParameters) - Constructor for class hex.deeplearning.DeepLearning
 
DeepLearning.DeepLearningDriver - Class in hex.deeplearning
 
DeepLearning.DeepLearningDriver() - Constructor for class hex.deeplearning.DeepLearning.DeepLearningDriver
 
DeepLearningBuilderHandler - Class in hex.api
 
DeepLearningBuilderHandler() - Constructor for class hex.api.DeepLearningBuilderHandler
 
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) - Constructor for class hex.deeplearning.DeepLearningModel
 
DeepLearningModel.DeepLearningModelInfo - Class in hex.deeplearning
 
DeepLearningModel.DeepLearningModelInfo() - Constructor for class hex.deeplearning.DeepLearningModel.DeepLearningModelInfo
 
DeepLearningModel.DeepLearningModelInfo(DeepLearningModel.DeepLearningParameters, DataInfo, boolean, Frame, Frame) - Constructor for class hex.deeplearning.DeepLearningModel.DeepLearningModelInfo
 
DeepLearningModel.DeepLearningModelOutput - Class in hex.deeplearning
 
DeepLearningModel.DeepLearningModelOutput() - Constructor for class hex.deeplearning.DeepLearningModel.DeepLearningModelOutput
 
DeepLearningModel.DeepLearningModelOutput(DeepLearning) - Constructor for class hex.deeplearning.DeepLearningModel.DeepLearningModelOutput
 
DeepLearningModel.DeepLearningParameters - Class in hex.deeplearning
 
DeepLearningModel.DeepLearningParameters() - Constructor for class hex.deeplearning.DeepLearningModel.DeepLearningParameters
 
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, MeanSquare, Huber for regression Absolute, MeanSquare, Huber or CrossEntropy for classification
DeepLearningModel.DeepLearningParameters.MissingValuesHandling - Enum in hex.deeplearning
 
DeepLearningModel.DeepLearningScoring - Class in hex.deeplearning
 
DeepLearningModel.DeepLearningScoring() - Constructor for class hex.deeplearning.DeepLearningModel.DeepLearningScoring
 
DeepLearningModelV3 - Class in hex.schemas
 
DeepLearningModelV3() - Constructor for class hex.schemas.DeepLearningModelV3
 
DeepLearningModelV3.DeepLearningModelOutputV3 - Class in hex.schemas
 
DeepLearningModelV3.DeepLearningModelOutputV3() - Constructor for class hex.schemas.DeepLearningModelV3.DeepLearningModelOutputV3
 
DeepLearningTask - Class in hex.deeplearning
 
DeepLearningTask(Key, DeepLearningModel.DeepLearningModelInfo, float) - Constructor for class hex.deeplearning.DeepLearningTask
 
DeepLearningTask2 - Class in hex.deeplearning
DRemoteTask-based Deep Learning.
DeepLearningTask2(Key, Frame, DeepLearningModel.DeepLearningModelInfo, float) - 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
 
DeepLearningV3.DeepLearningParametersV3() - Constructor for class hex.schemas.DeepLearningV3.DeepLearningParametersV3
 
DEFAULT_ABSTOL - Static variable in class hex.optimization.ADMM.L1Solver
 
DEFAULT_RELTOL - Static variable in class hex.optimization.ADMM.L1Solver
 
defaultLink - Variable in enum hex.glm.GLMModel.GLMParameters.Family
 
delete() - Method in class hex.deeplearning.DeepLearningModel
 
delete() - Method in class hex.word2vec.Word2VecModel
 
deleteProgressKey() - Method in class hex.pca.PCA.EmbeddedSVD
 
denormalizeBeta(double[]) - Method in class hex.DataInfo
 
dest - Variable in class hex.schemas.MakeGLMModelV3
 
deviance(double, double) - Method in class hex.glm.GLMModel.GLMParameters
 
deviance(float, float) - Method in class hex.glm.GLMModel.GLMParameters
 
devianceTest - Variable in class hex.glm.GLMModel.Submodel
 
devianceTrain - Variable in class hex.glm.GLMModel.Submodel
 
dfork(Frame) - Method in class hex.FrameTask
 
DHistogram<TDH extends DHistogram> - Class in hex.tree
A Histogram, computed in parallel over a Vec.
DHistogram(String, int, int, byte, float, float, long) - Constructor for class hex.tree.DHistogram
 
diagAvg() - Method in class hex.gram.Gram
 
diagMin() - Method in class hex.gram.Gram
 
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.
dinfo() - Method in class hex.FrameTask
 
dinfo() - Method in class hex.glm.GLMModel
 
distribution - Variable in class hex.schemas.GBMV3.GBMParametersV3
 
div(float) - Method in class hex.deeplearning.DeepLearningModel.DeepLearningModelInfo
 
div(float) - Method in class hex.word2vec.Word2VecModel.Word2VecModelInfo
Used to reduce the summations from map methods to an average across map/reduce threads.
do_not_split() - Method in class hex.tree.DTree.UndecidedNode
 
do_train(int, S) - Method in class hex.GridSearchHandler
 
doLineSearch(L_BFGS.GradientInfo, double[], double[], int, double) - Method in class hex.optimization.L_BFGS.GradientSolver
Perform line search at given solution and search direction.
doScoringAndSaveModel(boolean, boolean, boolean) - Method in class hex.tree.SharedTree
 
DRealHistogram - Class in hex.tree
A Histogram, computed in parallel over a Vec.
DRealHistogram(String, int, int, byte, float, float, long) - Constructor for class hex.tree.DRealHistogram
 
DRF - Class in hex.tree.drf
Gradient Boosted Trees Based on "Elements of Statistical Learning, Second Edition, page 387"
DRF(DRFModel.DRFParameters) - Constructor for class hex.tree.drf.DRF
 
DRFBuilderHandler - Class in hex.api
 
DRFBuilderHandler() - Constructor for class hex.api.DRFBuilderHandler
 
DRFGrid - Class in hex.tree.drf
A Grid of Models Used to explore Model hyper-parameter space.
DRFGrid() - Constructor for class hex.tree.drf.DRFGrid
FIXME: Rest API requirement - do not call directly
DRFGridSearchHandler - Class in hex.api
A specific handler for DRF grid search.
DRFGridSearchHandler() - Constructor for class hex.api.DRFGridSearchHandler
 
DRFGridSearchV3 - Class in hex.schemas
End-point for DRF grid search.
DRFGridSearchV3() - Constructor for class hex.schemas.DRFGridSearchV3
 
DRFModel - Class in hex.tree.drf
 
DRFModel(Key, DRFModel.DRFParameters, DRFModel.DRFOutput) - Constructor for class hex.tree.drf.DRFModel
 
DRFModel.DRFOutput - Class in hex.tree.drf
 
DRFModel.DRFOutput(DRF, double, double) - Constructor for class hex.tree.drf.DRFModel.DRFOutput
 
DRFModel.DRFParameters - Class in hex.tree.drf
 
DRFModel.DRFParameters() - Constructor for class hex.tree.drf.DRFModel.DRFParameters
 
DRFModelV3 - Class in hex.schemas
 
DRFModelV3() - Constructor for class hex.schemas.DRFModelV3
 
DRFModelV3.DRFModelOutputV3 - Class in hex.schemas
 
DRFModelV3.DRFModelOutputV3() - Constructor for class hex.schemas.DRFModelV3.DRFModelOutputV3
 
DRFV3 - Class in hex.schemas
 
DRFV3() - Constructor for class hex.schemas.DRFV3
 
DRFV3.DRFParametersV3 - Class in hex.schemas
 
DRFV3.DRFParametersV3() - Constructor for class hex.schemas.DRFV3.DRFParametersV3
 
dropIntercept() - Method in class hex.gram.Gram
 
Dropout - Class in hex.deeplearning
Helper class for dropout training of Neural Nets
DTree - Class in hex.tree
A Decision Tree, laid over a Frame of Vecs, and built distributed.
DTree(String[], int, char, char, char, int) - Constructor for class hex.tree.DTree
 
DTree(String[], int, char, char, char, int, long) - Constructor for class hex.tree.DTree
 
DTree.DecidedNode - Class in hex.tree
 
DTree.DecidedNode(DTree.UndecidedNode, DHistogram[]) - Constructor for class hex.tree.DTree.DecidedNode
 
DTree.LeafNode - Class in hex.tree
 
DTree.LeafNode(DTree, int) - Constructor for class hex.tree.DTree.LeafNode
 
DTree.LeafNode(DTree, int, int) - Constructor for class hex.tree.DTree.LeafNode
 
DTree.Node - Class in hex.tree
 
DTree.Split - Class in hex.tree
 
DTree.Split(int, int, IcedBitSet, byte, double, double, double, long, long, double, double) - Constructor for class hex.tree.DTree.Split
 
DTree.UndecidedNode - Class in hex.tree
 
DTree.UndecidedNode(DTree, int, DHistogram[]) - Constructor for class hex.tree.DTree.UndecidedNode
 
DTreeScorer<T extends DTreeScorer<T>> - Class in hex.tree
 
DTreeScorer(int, int, Key[][]) - Constructor for class hex.tree.DTreeScorer
 

E

eigenvectors - Variable in class hex.schemas.GLRMModelV3.GLRMModelOutputV3
 
eigenvectors - Variable in class hex.schemas.PCAModelV3.PCAModelOutputV3
 
end() - Method in class hex.deeplearning.Neurons.SparseVector
 
epoch_counter - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningScoring
 
epoch_counter - Variable in class hex.deeplearning.DeepLearningModel
 
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.Word2VecV3.Word2VecParametersV3
 
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).
error() - Method in class hex.deeplearning.DeepLearningModel
 
estimateRho(double, double, double, double) - Static method in class hex.optimization.ADMM.L1Solver
Estimate optimal rho based on l1 penalty and (estimate of) soltuion x without the l1penalty
etaOffset - Variable in class hex.DataInfo.Row
 
event_column - Variable in class hex.coxph.CoxPHModel.CoxPHParameters
 
Example - Class in hex.example
Example model builder...
Example(ExampleModel.ExampleParameters) - Constructor for class hex.example.Example
 
ExampleBuilderHandler - Class in hex.api
 
ExampleBuilderHandler() - Constructor for class hex.api.ExampleBuilderHandler
 
ExampleModel - Class in hex.example
 
ExampleModel.ExampleOutput - Class in hex.example
 
ExampleModel.ExampleOutput(Example) - Constructor for class hex.example.ExampleModel.ExampleOutput
 
ExampleModel.ExampleParameters - Class in hex.example
 
ExampleModel.ExampleParameters() - Constructor for class hex.example.ExampleModel.ExampleParameters
 
ExampleModelV3 - Class in hex.schemas
 
ExampleModelV3() - Constructor for class hex.schemas.ExampleModelV3
 
ExampleModelV3.ExampleModelOutputV3 - Class in hex.schemas
 
ExampleModelV3.ExampleModelOutputV3() - Constructor for class hex.schemas.ExampleModelV3.ExampleModelOutputV3
 
ExampleV3 - Class in hex.schemas
 
ExampleV3() - Constructor for class hex.schemas.ExampleV3
 
ExampleV3.ExampleParametersV3 - Class in hex.schemas
 
ExampleV3.ExampleParametersV3() - Constructor for class hex.schemas.ExampleV3.ExampleParametersV3
 
expandCats(double[][], DataInfo) - Static method in class hex.glrm.GLRM
 
explainedDev() - Method in class hex.glm.GLMValidation
 
export_weights_and_biases - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
 
extractDenseRow(Chunk[], int, DataInfo.Row) - Method in class hex.DataInfo
 
extractSparseRows(Chunk[], double[]) - Method in class hex.DataInfo
Extract (sparse) rows from given chunks.

F

family - Variable in class hex.schemas.GLMV3.GLMParametersV3
 
fast_mode - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
Enable fast mode (minor approximation in back-propagation), should not affect results significantly.
fillBytes(long) - Method in class hex.deeplearning.Dropout
 
fillFromImpl(G) - Method in class hex.GridSearchSchema
 
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(KMeansModel.KMeansOutput) - Method in class hex.schemas.KMeansModelV3.KMeansModelOutputV3
 
fillFromParms(Properties) - Method in class hex.GridSearchSchema
 
filterExpandedColumns(int[]) - Method in class hex.DataInfo
 
find_maxEx() - Method in class hex.tree.DHistogram
 
find_maxEx(float, int) - Static method in class hex.tree.DHistogram
 
find_maxIn() - Method in class hex.tree.DHistogram
 
find_min() - Method in class hex.tree.DHistogram
 
findSynonyms(String, int) - Method in class hex.word2vec.Word2VecModel
Find synonyms (i.e.
findSynonyms(float[], int) - Method in class hex.word2vec.Word2VecModel
Find synonyms (i.e.
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.
formGram(double[][], boolean) - Static method in class hex.pca.PCA
Given a n by k matrix X, form its Gram matrix
formGram(double[][]) - Static method in class hex.pca.PCA
 
fprop(long, boolean) - Method in class hex.deeplearning.Neurons
Forward propagation
fprop(long, boolean) - Method in class hex.deeplearning.Neurons.Input
 
fprop() - Method in class hex.deeplearning.Neurons.Linear
 
fprop(long, boolean) - Method in class hex.deeplearning.Neurons.Maxout
 
fprop(long, boolean) - Method in class hex.deeplearning.Neurons.MaxoutDropout
 
fprop(long, boolean) - Method in class hex.deeplearning.Neurons.Output
 
fprop(long, boolean) - Method in class hex.deeplearning.Neurons.Rectifier
 
fprop(long, boolean) - Method in class hex.deeplearning.Neurons.RectifierDropout
 
fprop() - Method in class hex.deeplearning.Neurons.Softmax
 
fprop(long, boolean) - Method in class hex.deeplearning.Neurons.Tanh
 
fprop(long, boolean) - Method in class hex.deeplearning.Neurons.TanhDropout
 
FrameTask<T extends FrameTask<T>> - Class in hex
 
FrameTask(Key, DataInfo) - Constructor for class hex.FrameTask
 
FrameTask(Key, DataInfo, H2O.H2OCountedCompleter) - Constructor for class hex.FrameTask
 
FrameTask(Key, Key, int[]) - Constructor for class hex.FrameTask
 
FrameTask(Key, Key, int[], H2O.H2OCountedCompleter) - Constructor for class hex.FrameTask
 
FrameTask(FrameTask) - Constructor for class hex.FrameTask
 
frobenius2(double[][]) - Static method in class hex.glrm.GLRM
 
fullN() - Method in class hex.DataInfo
 
fullN() - Method in class hex.gram.Gram
 

G

gamma_x - Variable in class hex.schemas.GLRMV3.GLRMParametersV3
 
gamma_y - Variable in class hex.schemas.GLRMV3.GLRMParametersV3
 
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
 
GBMBuilderHandler - Class in hex.api
 
GBMBuilderHandler() - Constructor for class hex.api.GBMBuilderHandler
 
GBMGrid - Class in hex.tree.gbm
A Grid of Models Used to explore Model hyper-parameter space.
GBMGrid() - Constructor for class hex.tree.gbm.GBMGrid
FIXME: Rest API requirement - do not call directly
GBMGridSearchHandler - Class in hex.api
A specific handler for GBM grid search.
GBMGridSearchHandler() - Constructor for class hex.api.GBMGridSearchHandler
 
GBMGridSearchV3 - Class in hex.schemas
End-point for GBM grid search.
GBMGridSearchV3() - Constructor for class hex.schemas.GBMGridSearchV3
 
GBMModel - Class in hex.tree.gbm
 
GBMModel(Key, GBMModel.GBMParameters, GBMModel.GBMOutput) - Constructor for class hex.tree.gbm.GBMModel
 
GBMModel.GBMOutput - Class in hex.tree.gbm
 
GBMModel.GBMOutput(GBM, double, double) - Constructor for class hex.tree.gbm.GBMModel.GBMOutput
 
GBMModel.GBMParameters - Class in hex.tree.gbm
 
GBMModel.GBMParameters() - Constructor for class hex.tree.gbm.GBMModel.GBMParameters
 
GBMModel.GBMParameters.Family - Enum in hex.tree.gbm
Distribution functions.
GBMModelV3 - Class in hex.schemas
 
GBMModelV3() - Constructor for class hex.schemas.GBMModelV3
 
GBMModelV3.GBMModelOutputV3 - Class in hex.schemas
 
GBMModelV3.GBMModelOutputV3() - Constructor for class hex.schemas.GBMModelV3.GBMModelOutputV3
 
GBMV3 - Class in hex.schemas
 
GBMV3() - Constructor for class hex.schemas.GBMV3
 
GBMV3.GBMParametersV3 - Class in hex.schemas
 
GBMV3.GBMParametersV3() - Constructor for class hex.schemas.GBMV3.GBMParametersV3
 
generateSummary(Key, int) - Method in class hex.glm.GLMModel
Re-do the TwoDim table generation with updated model.
get(int, int) - Method in class hex.deeplearning.Neurons.DenseColMatrix
 
get(int, int) - Method in class hex.deeplearning.Neurons.DenseRowMatrix
 
get(int) - Method in class hex.deeplearning.Neurons.DenseVector
 
get(int, int) - Method in interface hex.deeplearning.Neurons.Matrix
 
get(int, int) - Method in class hex.deeplearning.Neurons.SparseRowMatrix
 
get(int) - Method in class hex.deeplearning.Neurons.SparseVector
Slow path access to i-th element
get(int) - Method in interface hex.deeplearning.Neurons.Vector
 
get(int, int) - Method in class hex.gram.Gram
 
get(Frame) - Static method in class hex.kmeans.KMeansGrid
 
get(Frame) - Static method in class hex.tree.drf.DRFGrid
 
get(Frame) - Static method in class hex.tree.gbm.GBMGrid
 
get_ada_dx_g(int) - Method in class hex.deeplearning.DeepLearningModel.DeepLearningModelInfo
 
get_avg_activations(int) - Method in class hex.deeplearning.DeepLearningModel.DeepLearningModelInfo
 
get_biases(int) - Method in class hex.deeplearning.DeepLearningModel.DeepLearningModelInfo
 
get_biases_ada_dx_g(int) - Method in class hex.deeplearning.DeepLearningModel.DeepLearningModelInfo
 
get_biases_momenta(int) - Method in class hex.deeplearning.DeepLearningModel.DeepLearningModelInfo
 
get_params() - Method in class hex.coxph.CoxPHModel
 
get_params() - Method in class hex.deeplearning.DeepLearningModel.DeepLearningModelInfo
 
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_processed_global() - Method in class hex.deeplearning.DeepLearningModel.DeepLearningModelInfo
 
get_processed_local() - Method in class hex.deeplearning.DeepLearningModel.DeepLearningModelInfo
 
get_processed_total() - Method in class hex.deeplearning.DeepLearningModel.DeepLearningModelInfo
 
get_weights(int) - Method in class hex.deeplearning.DeepLearningModel.DeepLearningModelInfo
 
get_weights_momenta(int) - Method in class hex.deeplearning.DeepLearningModel.DeepLearningModelInfo
 
getBeta(int, double[]) - Method in class hex.glm.GLMModel.GLMOutput
 
getCategoricalId(int, int) - Method in class hex.DataInfo
 
getDenseXX() - Method in class hex.gram.Gram
 
getGloballyProcessed() - Method in class hex.word2vec.Word2VecModel.Word2VecModelInfo
 
getGradient(double[]) - Method in class hex.glm.GLM.GLMGradientSolver
 
getGradient(double[]) - Method in class hex.glm.GLM.ProximalGradientSolver
 
getGradient(double[]) - Method in class hex.optimization.L_BFGS.GradientSolver
Evaluate gradient at solution beta.
getHypers(KMeansModel.KMeansParameters) - Method in class hex.kmeans.KMeansGrid
 
getHypers(DRFModel.DRFParameters) - Method in class hex.tree.drf.DRFGrid
 
getHypers(GBMModel.GBMParameters) - Method in class hex.tree.gbm.GBMGrid
 
getHypers(SharedTreeModel.SharedTreeParameters, double[]) - Method in class hex.tree.SharedTreeGrid
 
getInstance() - Static method in class hex.deeplearning.MurmurHash
 
getL() - Method in class hex.gram.Gram.Cholesky
 
getL() - Method in class hex.gram.Gram.InPlaceCholesky
 
getLocallyProcessed() - Method in class hex.word2vec.Word2VecModel.Word2VecModelInfo
 
getModelCategory() - Method in class hex.deeplearning.DeepLearningModel.DeepLearningModelOutput
 
getModelCategory() - Method in class hex.example.ExampleModel.ExampleOutput
 
getModelCategory() - Method in class hex.glrm.GLRMModel.GLRMOutput
 
getModelCategory() - Method in class hex.grep.GrepModel.GrepOutput
 
getModelCategory() - Method in class hex.pca.PCAModel.PCAOutput
 
getModelCategory() - Method in class hex.svd.SVDModel.SVDOutput
 
getModelCategory() - Method in class hex.word2vec.Word2VecModel.Word2VecOutput
 
getModelInfo() - Method in class hex.word2vec.Word2VecModel
 
getModelInfo() - Method in class hex.word2vec.WordVectorTrainer
 
getNormBeta() - Method in class hex.glm.GLMModel.GLMOutput
 
getNumFolds() - Method in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
 
getObjVals(double[], double[], int, double) - Method in class hex.glm.GLM.GLMGradientSolver
 
getObjVals(double[], double[], int, double) - Method in class hex.glm.GLM.ProximalGradientSolver
 
getObjVals(double[], double[], int, double) - Method in class hex.optimization.L_BFGS.GradientSolver
Evaluate objective values at k line search points beta_k.
getParams() - Method in class hex.word2vec.Word2VecModel.Word2VecModelInfo
 
getPublishedKeys() - Method in class hex.tree.SharedTreeModel
 
getSearchDirection(double[]) - Method in class hex.optimization.L_BFGS.History
 
getTotalProcessed() - Method in class hex.word2vec.Word2VecModel.Word2VecModelInfo
 
getXX() - Method in class hex.gram.Gram.Cholesky
 
getXX() - Method in class hex.gram.Gram
 
ginfo - Variable in class hex.optimization.L_BFGS.Result
 
GLM - Class in hex.glm
Created by tomasnykodym on 8/27/14.
GLM(Key, String, GLMModel.GLMParameters) - Constructor for class hex.glm.GLM
 
GLM(GLMModel.GLMParameters) - Constructor for class hex.glm.GLM
 
GLM.BetaConstraint - Class in hex.glm
 
GLM.BetaConstraint() - Constructor for class hex.glm.GLM.BetaConstraint
 
GLM.GLMDriver - Class in hex.glm
Contains implementation of the glm algo.
GLM.GLMDriver(H2O.H2OCountedCompleter) - Constructor for class hex.glm.GLM.GLMDriver
 
GLM.GLMGradientInfo - Class in hex.glm
 
GLM.GLMGradientInfo(double, double, double[]) - Constructor for class hex.glm.GLM.GLMGradientInfo
 
GLM.GLMGradientSolver - Class in hex.glm
Gradient and line search computation for L_BFGS and also L_BFGS solver wrapper (for ADMM)
GLM.GLMGradientSolver(GLMModel.GLMParameters, DataInfo, double, double, double) - Constructor for class hex.glm.GLM.GLMGradientSolver
 
GLM.GLMGradientSolver(GLMModel.GLMParameters, DataInfo, double, double, double, Vec) - Constructor for class hex.glm.GLM.GLMGradientSolver
 
GLM.GLMSingleLambdaTsk - Class in hex.glm
Task to compute GLM solution for a particular (single) lambda value.
GLM.GLMSingleLambdaTsk(H2O.H2OCountedCompleter, GLM.GLMTaskInfo) - Constructor for class hex.glm.GLM.GLMSingleLambdaTsk
 
GLM.GLMTaskInfo - Class in hex.glm
Encapsulates state of the computation.
GLM.GLMTaskInfo(Key, int, long, double, double, double, double[], int, GLM.GLMGradientInfo, double) - Constructor for class hex.glm.GLM.GLMTaskInfo
 
GLM.GramSolver - Class in hex.glm
Created by tomasnykodym on 3/30/15.
GLM.GramSolver(Gram, double[], double, double, boolean) - Constructor for class hex.glm.GLM.GramSolver
 
GLM.GramSolver(Gram, double[], boolean, double, double, double[], double[], double, double[], double[]) - Constructor for class hex.glm.GLM.GramSolver
 
GLM.LBFGS_ProximalSolver - Class in hex.glm
 
GLM.LBFGS_ProximalSolver(L_BFGS.GradientSolver, double[], double[], L_BFGS.ProgressMonitor) - Constructor for class hex.glm.GLM.LBFGS_ProximalSolver
 
GLM.ProximalGradientInfo - Class in hex.glm
 
GLM.ProximalGradientInfo(L_BFGS.GradientInfo, double, double[]) - Constructor for class hex.glm.GLM.ProximalGradientInfo
 
GLM.ProximalGradientSolver - Class in hex.glm
Simple wrapper around gradient computation, adding proximal penalty
GLM.ProximalGradientSolver(L_BFGS.GradientSolver, double[], double[]) - Constructor for class hex.glm.GLM.ProximalGradientSolver
 
GLMBuilderHandler - Class in hex.api
 
GLMBuilderHandler() - Constructor for class hex.api.GLMBuilderHandler
 
GLMModel - Class in hex.glm
Created by tomasnykodym on 8/27/14.
GLMModel(Key, GLMModel.GLMParameters, GLM, double, double, double, long, boolean, boolean) - Constructor for class hex.glm.GLMModel
 
GLMModel.GLMOutput - Class in hex.glm
 
GLMModel.GLMOutput(DataInfo, String[], String[][], String[], boolean) - Constructor for class hex.glm.GLMModel.GLMOutput
 
GLMModel.GLMOutput() - Constructor for class hex.glm.GLMModel.GLMOutput
 
GLMModel.GLMOutput(GLM) - Constructor for class hex.glm.GLMModel.GLMOutput
 
GLMModel.GLMParameters - Class in hex.glm
 
GLMModel.GLMParameters() - Constructor for class hex.glm.GLMModel.GLMParameters
 
GLMModel.GLMParameters(GLMModel.GLMParameters.Family) - Constructor for class hex.glm.GLMModel.GLMParameters
 
GLMModel.GLMParameters(GLMModel.GLMParameters.Family, GLMModel.GLMParameters.Link) - Constructor for class hex.glm.GLMModel.GLMParameters
 
GLMModel.GLMParameters(GLMModel.GLMParameters.Family, GLMModel.GLMParameters.Link, double[], double[]) - Constructor for class hex.glm.GLMModel.GLMParameters
 
GLMModel.GLMParameters(GLMModel.GLMParameters.Family, double[], double[], double, double) - Constructor for class hex.glm.GLMModel.GLMParameters
 
GLMModel.GLMParameters.Family - Enum in hex.glm
 
GLMModel.GLMParameters.Link - Enum in hex.glm
 
GLMModel.GLMParameters.Solver - Enum in hex.glm
 
GLMModel.Submodel - Class in hex.glm
 
GLMModel.Submodel(double, double[], int, double, double) - Constructor for class hex.glm.GLMModel.Submodel
 
GLMModelV3 - Class in hex.schemas
 
GLMModelV3() - Constructor for class hex.schemas.GLMModelV3
 
GLMModelV3.GLMModelOutputV3 - Class in hex.schemas
 
GLMModelV3.GLMModelOutputV3() - Constructor for class hex.schemas.GLMModelV3.GLMModelOutputV3
 
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.GLMCoordinateDescentTask - Class in hex.glm
 
GLMTask.GLMCoordinateDescentTask(double[], double[], double, double, double, double) - Constructor for class hex.glm.GLMTask.GLMCoordinateDescentTask
 
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.GLMIterationTask(Key, DataInfo, double, GLMModel.GLMParameters, boolean, double[], double, Vec, H2O.H2OCountedCompleter) - Constructor for class hex.glm.GLMTask.GLMIterationTask
 
GLMTask.LBFGS_LogisticGradientTask - Class in hex.glm
Tassk with simplified gradient computation for logistic regression (and least squares) Looks like
GLMTask.LBFGS_LogisticGradientTask(DataInfo, GLMModel.GLMParameters, double, double[], double, Vec) - Constructor for class hex.glm.GLMTask.LBFGS_LogisticGradientTask
 
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
 
GLMV3.GLMParametersV3() - Constructor for class hex.schemas.GLMV3.GLMParametersV3
 
GLMValidation - Class in hex.glm
Class for GLMValidation.
GLMValidation(String[], boolean, double, GLMModel.GLMParameters, int, double, boolean) - Constructor for class hex.glm.GLMValidation
 
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.Initialization - Enum in hex.glrm
 
GLRMBuilderHandler - Class in hex.api
 
GLRMBuilderHandler() - Constructor for class hex.api.GLRMBuilderHandler
 
GLRMModel - Class in hex.glrm
 
GLRMModel(Key, GLRMModel.GLRMParameters, GLRMModel.GLRMOutput) - Constructor for class hex.glrm.GLRMModel
 
GLRMModel.GLRMOutput - Class in hex.glrm
 
GLRMModel.GLRMOutput(GLRM) - Constructor for class hex.glrm.GLRMModel.GLRMOutput
 
GLRMModel.GLRMParameters - Class in hex.glrm
 
GLRMModel.GLRMParameters() - Constructor for class hex.glrm.GLRMModel.GLRMParameters
 
GLRMModel.GLRMParameters.Loss - Enum in hex.glrm
 
GLRMModel.GLRMParameters.MultiLoss - Enum in hex.glrm
 
GLRMModel.GLRMParameters.Regularizer - Enum in hex.glrm
 
GLRMModel.ModelMetricsGLRM - Class in hex.glrm
 
GLRMModel.ModelMetricsGLRM(Model, Frame) - Constructor for class hex.glrm.GLRMModel.ModelMetricsGLRM
 
GLRMModel.ModelMetricsGLRM.GLRMModelMetrics - Class in hex.glrm
 
GLRMModel.ModelMetricsGLRM.GLRMModelMetrics(int) - Constructor for class hex.glrm.GLRMModel.ModelMetricsGLRM.GLRMModelMetrics
 
GLRMModelV3 - Class in hex.schemas
 
GLRMModelV3() - Constructor for class hex.schemas.GLRMModelV3
 
GLRMModelV3.GLRMModelOutputV3 - Class in hex.schemas
 
GLRMModelV3.GLRMModelOutputV3() - Constructor for class hex.schemas.GLRMModelV3.GLRMModelOutputV3
 
GLRMV3 - Class in hex.schemas
 
GLRMV3() - Constructor for class hex.schemas.GLRMV3
 
GLRMV3.GLRMParametersV3 - Class in hex.schemas
 
GLRMV3.GLRMParametersV3() - Constructor for class hex.schemas.GLRMV3.GLRMParametersV3
 
goByCols(Chunk[], boolean[]) - Method in class hex.glm.GLMTask.LBFGS_LogisticGradientTask
 
goByRows(Chunk[], boolean[]) - Method in class hex.glm.GLMTask.LBFGS_LogisticGradientTask
 
gradient(double[]) - Method in class hex.glm.GLM.GramSolver
 
gradient(double[]) - Method in class hex.glm.GLM.LBFGS_ProximalSolver
 
gradient(double[]) - Method in interface hex.optimization.ADMM.ProximalSolver
 
gradient_epsilon - Variable in class hex.schemas.GLMV3.GLMParametersV3
 
gradientCheck(double, double) - Method in class hex.glm.GLM.GLMTaskInfo
 
Gram - Class in hex.gram
 
Gram() - Constructor for class hex.gram.Gram
 
Gram(int, int, int, int, boolean) - Constructor for class hex.gram.Gram
 
Gram(Gram) - Constructor for class hex.gram.Gram
 
Gram(double[][]) - Constructor for class hex.gram.Gram
 
Gram.Cholesky - Class in hex.gram
 
Gram.Cholesky(double[][], double[]) - Constructor for class hex.gram.Gram.Cholesky
 
Gram.Cholesky(Gram) - Constructor for class hex.gram.Gram.Cholesky
 
Gram.Cholesky.DelayedTask - Class in hex.gram
 
Gram.Cholesky.DelayedTask(int) - Constructor for class hex.gram.Gram.Cholesky.DelayedTask
 
Gram.Cholesky.ParSolver - Class 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.GramTask(Key, DataInfo) - Constructor for class hex.gram.Gram.GramTask
 
Gram.InPlaceCholesky - Class in hex.gram
 
Gram.NonSPDMatrixException - Exception in hex.gram
 
Gram.NonSPDMatrixException() - Constructor for exception hex.gram.Gram.NonSPDMatrixException
 
Grep - Class in hex.grep
Grep model builder...
Grep(GrepModel.GrepParameters) - Constructor for class hex.grep.Grep
 
GrepBuilderHandler - Class in hex.api
 
GrepBuilderHandler() - Constructor for class hex.api.GrepBuilderHandler
 
GrepModel - Class in hex.grep
 
GrepModel.GrepOutput - Class in hex.grep
 
GrepModel.GrepOutput(Grep) - Constructor for class hex.grep.GrepModel.GrepOutput
 
GrepModel.GrepParameters - Class in hex.grep
 
GrepModel.GrepParameters() - Constructor for class hex.grep.GrepModel.GrepParameters
 
GrepModelV3 - Class in hex.schemas
 
GrepModelV3() - Constructor for class hex.schemas.GrepModelV3
 
GrepModelV3.GrepModelOutputV3 - Class in hex.schemas
 
GrepModelV3.GrepModelOutputV3() - Constructor for class hex.schemas.GrepModelV3.GrepModelOutputV3
 
GrepV3 - Class in hex.schemas
 
GrepV3() - Constructor for class hex.schemas.GrepV3
 
GrepV3.GrepParametersV3 - Class in hex.schemas
 
GrepV3.GrepParametersV3() - Constructor for class hex.schemas.GrepV3.GrepParametersV3
 
grid_parameters - Variable in class hex.GridSearchSchema
 
GridSearchHandler<G extends hex.Grid<MP,G>,S extends GridSearchSchema<G,S,MP,P>,MP extends hex.Model.Parameters,P extends water.api.ModelParametersSchema> - Class in hex
FIXME: how to get rid of P, since it is already enforced by S
GridSearchHandler() - Constructor for class hex.GridSearchHandler
 
GridSearchSchema<G extends hex.Grid<MP,G>,S extends GridSearchSchema<G,S,MP,P>,MP extends hex.Model.Parameters,P extends water.api.ModelParametersSchema> - Class in hex
This is a common grid search schema composed of two parameters: default parameters for a builder and hyper parameters which are given as a mapping from parameter name to list of possible values.
GridSearchSchema() - Constructor for class hex.GridSearchSchema
 

H

hasBounds() - Method in class hex.glm.GLM.BetaConstraint
 
hasGradient() - Method in class hex.glm.GLM.GramSolver
 
hasGradient() - Method in class hex.glm.GLM.LBFGS_ProximalSolver
 
hasGradient() - Method in interface hex.optimization.ADMM.ProximalSolver
 
hash(byte[], int, int) - Method in class hex.deeplearning.MurmurHash
 
hasNaNsOrInf() - Method in class hex.glm.GLMTask.GLMIterationTask
 
hasNaNsOrInfs() - Method in class hex.gram.Gram
 
hasNaNsOrInfs() - Method in class hex.optimization.L_BFGS.GradientInfo
 
hex - package hex
 
hex.api - package hex.api
 
hex.coxph - package hex.coxph
 
hex.deeplearning - package hex.deeplearning
 
hex.example - package hex.example
 
hex.glm - package hex.glm
 
hex.glrm - package hex.glrm
 
hex.gram - package hex.gram
 
hex.grep - package hex.grep
 
hex.kmeans - package hex.kmeans
 
hex.naivebayes - package hex.naivebayes
 
hex.optimization - package hex.optimization
 
hex.pca - package hex.pca
 
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.gbm - package hex.tree.gbm
 
hex.word2vec - package hex.word2vec
 
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.
HYPER_DEFAULTS - Static variable in class hex.tree.SharedTreeGrid
 
HYPER_NAMES - Static variable in class hex.tree.SharedTreeGrid
 
hyperDefaults() - Method in class hex.kmeans.KMeansGrid
 
hyperDefaults() - Method in class hex.tree.drf.DRFGrid
 
hyperDefaults() - Method in class hex.tree.gbm.GBMGrid
 
hyperNames() - Method in class hex.kmeans.KMeansGrid
 
hyperNames() - Method in class hex.tree.drf.DRFGrid
 
hyperNames() - Method in class hex.tree.gbm.GBMGrid
 

I

idx_nids(int) - Method in class hex.tree.SharedTree
 
idx_oobt() - Method in class hex.tree.SharedTree
 
idx_resp() - Method in class hex.tree.SharedTree
 
idx_tree(int) - 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
 
idx_ycat(int, int, DataInfo) - Static method in class hex.glrm.GLRM
 
idx_ynum(int, DataInfo) - Static method in class hex.glrm.GLRM
 
idxs - Variable in class hex.glm.GLMModel.Submodel
 
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.
inc(long) - Method in class hex.word2vec.WordCountTask.ValueStringCount
 
inc() - Method in class hex.word2vec.WordCountTask.ValueStringCount
 
init(boolean) - Method in class hex.coxph.CoxPH
Initialize the ModelBuilder, validating all arguments and preparing the training frame.
init - Variable in class hex.coxph.CoxPHModel.CoxPHParameters
 
init(boolean) - Method in class hex.deeplearning.DeepLearning
Initialize the ModelBuilder, validating all arguments and preparing the training frame.
init(Neurons[], int, DeepLearningModel.DeepLearningParameters, DeepLearningModel.DeepLearningModelInfo, boolean) - Method in class hex.deeplearning.Neurons
Initialization of the parameters and connectivity of a Neuron layer
init(boolean) - Method in class hex.example.Example
Initialize the ModelBuilder, validating all arguments and preparing the training frame.
init(boolean) - Method in class hex.glm.GLM
 
init(boolean) - Method in class hex.glrm.GLRM
 
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.kmeans.KMeans
Initialize the ModelBuilder, validating all arguments and preparing the training frame.
init(boolean) - Method in class hex.naivebayes.NaiveBayes
 
init(boolean) - Method in class hex.pca.PCA
 
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(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.SharedTree
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_step_size - Variable in class hex.schemas.GLRMV3.GLRMParametersV3
 
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.
initialHist(Frame, int, int, int, DHistogram[], boolean) - Static method in class hex.tree.DHistogram
 
initLearningRate - Variable in class hex.schemas.Word2VecV3.Word2VecParametersV3
 
initStats(CoxPHModel, DataInfo) - Method in class hex.coxph.CoxPH.CoxPHDriver
 
innerProduct(double[]) - Method in class hex.DataInfo.Row
 
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).
intercept - Variable in class hex.schemas.GLMV3.GLMParametersV3
 
isConstantResponse() - Method in class hex.tree.DHistogram
 
isDecidedRow(int) - Static method in class hex.tree.ScoreBuildHistogram
 
isOOBRow(int) - Static method in class hex.tree.ScoreBuildHistogram
 
isRootNode(DTree.Node) - Static method in class hex.tree.DTree
 
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
 
isSupervised() - Method in class hex.deeplearning.DeepLearning
 
isSupervised() - Method in class hex.deeplearning.DeepLearningModel.DeepLearningModelOutput
 
isSupervised() - Method in class hex.glm.GLM
 
isSupervised() - Method in class hex.naivebayes.NaiveBayes
 
isSupervised() - Method in class hex.tree.SharedTree
 
isValid() - Method in class hex.optimization.L_BFGS.GradientInfo
 
isValid() - Method in class hex.tree.TreeStats
 
iter() - Method in class hex.glm.GLM.GramSolver
 
iter() - Method in class hex.glm.GLM.LBFGS_ProximalSolver
 
iter() - Method in interface hex.optimization.ADMM.ProximalSolver
 
iter - Variable in class hex.optimization.L_BFGS.Result
 
iter_max - Variable in class hex.coxph.CoxPHModel.CoxPHParameters
 
iteration - Variable in class hex.glm.GLMModel.Submodel
 
iterations - Variable in class hex.schemas.ExampleModelV3.ExampleModelOutputV3
 
iterations - Variable in class hex.schemas.GLRMModelV3.GLRMModelOutputV3
 

J

job - Variable in class hex.GridSearchSchema
 

K

k() - Method in class hex.optimization.L_BFGS
 
k - Variable in class hex.schemas.GLRMV3.GLRMParametersV3
 
k - Variable in class hex.schemas.PCAV3.PCAParametersV3
 
keep_u - Variable in class hex.schemas.SVDV3.SVDParametersV3
 
key - Variable in class hex.schemas.SynonymV3
 
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(Key, String, KMeansModel.KMeansParameters) - Constructor for class hex.kmeans.KMeans
 
KMeans(KMeansModel.KMeansParameters) - Constructor for class hex.kmeans.KMeans
 
KMeans.Initialization - Enum in hex.kmeans
 
KMeansBuilderHandler - Class in hex.api
 
KMeansBuilderHandler() - Constructor for class hex.api.KMeansBuilderHandler
 
KMeansGrid - Class in hex.kmeans
A Grid of Models Used to explore Model hyper-parameter space.
KMeansGrid() - Constructor for class hex.kmeans.KMeansGrid
FIXME: Rest API requirement - do not call directly
KMeansGridSearchHandler - Class in hex.api
A specific handler for GBM grid search.
KMeansGridSearchHandler() - Constructor for class hex.api.KMeansGridSearchHandler
 
KMeansGridSearchV3 - Class in hex.schemas
End-point for KMeans grid search.
KMeansGridSearchV3() - Constructor for class hex.schemas.KMeansGridSearchV3
 
KMeansModel - Class in hex.kmeans
 
KMeansModel(Key, KMeansModel.KMeansParameters, KMeansModel.KMeansOutput) - Constructor for class hex.kmeans.KMeansModel
 
KMeansModel.KMeansOutput - Class in hex.kmeans
 
KMeansModel.KMeansOutput(KMeans) - Constructor for class hex.kmeans.KMeansModel.KMeansOutput
 
KMeansModel.KMeansParameters - Class in hex.kmeans
 
KMeansModel.KMeansParameters() - Constructor for class hex.kmeans.KMeansModel.KMeansParameters
 
KMeansModelV3 - Class in hex.schemas
 
KMeansModelV3() - Constructor for class hex.schemas.KMeansModelV3
 
KMeansModelV3.KMeansModelOutputV3 - Class in hex.schemas
 
KMeansModelV3.KMeansModelOutputV3() - Constructor for class hex.schemas.KMeansModelV3.KMeansModelOutputV3
 
KMeansV3 - Class in hex.schemas
 
KMeansV3() - Constructor for class hex.schemas.KMeansV3
 
KMeansV3.KMeansParametersV3 - Class in hex.schemas
 
KMeansV3.KMeansParametersV3() - Constructor for class hex.schemas.KMeansV3.KMeansParametersV3
 

L

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.
l1norm(double[]) - Method in class hex.glm.GLM.GLMSingleLambdaTsk
 
l2 - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
A regularization method that constrdains the sum of the squared weights.
L_BFGS - Class in hex.optimization
Created by tomasnykodym on 9/15/14.
L_BFGS() - Constructor for class hex.optimization.L_BFGS
 
L_BFGS.GradientInfo - Class in hex.optimization
 
L_BFGS.GradientInfo(double, double[]) - Constructor for class hex.optimization.L_BFGS.GradientInfo
 
L_BFGS.GradientSolver - Class in hex.optimization
Provides gradient computation and line search evaluation specific to given problem.
L_BFGS.GradientSolver() - Constructor for class hex.optimization.L_BFGS.GradientSolver
 
L_BFGS.History - Class in hex.optimization
Keeps L-BFGS history ie curvature information recorded over the last m steps.
L_BFGS.History(int, int) - Constructor for class hex.optimization.L_BFGS.History
 
L_BFGS.LineSearchSol - Class in hex.optimization
Line search results.
L_BFGS.LineSearchSol(boolean, double, double) - Constructor for class hex.optimization.L_BFGS.LineSearchSol
 
L_BFGS.ProgressMonitor - Class in hex.optimization
Monitor progress and enable early termination.
L_BFGS.ProgressMonitor() - Constructor for class hex.optimization.L_BFGS.ProgressMonitor
 
L_BFGS.Result - Class in hex.optimization
 
L_BFGS.Result(boolean, int, double[], L_BFGS.GradientInfo) - Constructor for class hex.optimization.L_BFGS.Result
 
lambda - Variable in class hex.schemas.GLMV3.GLMParametersV3
 
lambda_min_ratio - Variable in class hex.schemas.GLMV3.GLMParametersV3
 
lambda_search - Variable in class hex.schemas.GLMV3.GLMParametersV3
 
lambda_value - Variable in class hex.glm.GLMModel.Submodel
 
laplace - Variable in class hex.schemas.NaiveBayesV3.NaiveBayesParametersV3
 
largestCat() - Method in class hex.DataInfo
 
leaf(float) - Method in class hex.tree.TreeVisitor
 
learn_rate - Variable in class hex.schemas.GBMV3.GBMParametersV3
 
len() - Method in class hex.tree.DTree
 
levels - Variable in class hex.schemas.NaiveBayesModelV3.NaiveBayesModelOutputV3
 
lgrad(double, double) - Method in class hex.glrm.GLRMModel.GLRMParameters
 
likelihood(double, double) - Method in class hex.glm.GLMModel.GLMParameters
 
link(double) - Method in class hex.glm.GLMModel.GLMParameters
 
link - Variable in class hex.schemas.GLMV3.GLMParametersV3
 
linkDeriv(double) - Method in class hex.glm.GLMModel.GLMParameters
 
linkInv(double) - Method in class hex.glm.GLMModel.GLMParameters
 
linkInvDeriv(double) - Method in class hex.glm.GLMModel.GLMParameters
 
loading_key - Variable in class hex.schemas.GLRMModelV3.GLRMModelOutputV3
 
loading_key - Variable in class hex.schemas.GLRMV3.GLRMParametersV3
 
loading_key - Variable in class hex.schemas.PCAModelV3.PCAModelOutputV3
 
loading_name - Variable in class hex.schemas.PCAV3.PCAParametersV3
 
logloss() - Method in class hex.deeplearning.DeepLearningModel
 
loss(double, double) - Method in class hex.glrm.GLRMModel.GLRMParameters
 
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
 
lre_min - Variable in class hex.coxph.CoxPHModel.CoxPHParameters
 

M

madeProgress - Variable in class hex.optimization.L_BFGS.LineSearchSol
 
make(String, int, int, byte, float, float, long, boolean) - Static method in class hex.tree.DHistogram
 
make_model(int, MakeGLMModelV3) - Method in class hex.api.MakeGLMModelHandler
 
makeDecided(DTree.UndecidedNode, DHistogram[]) - Method in class hex.tree.drf.DRF
 
makeDecided(DTree.UndecidedNode, DHistogram[]) - Method in class hex.tree.gbm.GBM
 
makeDecided(DTree.UndecidedNode, DHistogram[]) - Method in class hex.tree.SharedTree
 
makeEmpty(int) - Static method in class hex.DataInfo
 
makeGLMModel(GLMModel.GLMParameters.Family, double[], String[], String) - Static method in class hex.glm.GLMModel
Make GLM model with given coefficients (predictors can be numeric only at the moment) Example: @see GLMTest.testMakeModel().
MakeGLMModelHandler - Class in hex.api
Created by tomasnykodym on 3/25/15.
MakeGLMModelHandler() - Constructor for class hex.api.MakeGLMModelHandler
 
MakeGLMModelV3 - Class in hex.schemas
Created by tomasnykodym on 8/29/14.
MakeGLMModelV3() - Constructor for class hex.schemas.MakeGLMModelV3
 
makeMetricBuilder(String[]) - Method in class hex.coxph.CoxPHModel
 
makeMetricBuilder(String[]) - Method in class hex.deeplearning.DeepLearningModel
 
makeMetricBuilder(String[]) - Method in class hex.example.ExampleModel
 
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.kmeans.KMeansModel
 
makeMetricBuilder(String[]) - Method in class hex.naivebayes.NaiveBayesModel
 
makeMetricBuilder(String[]) - Method in class hex.pca.PCAModel
 
makeMetricBuilder(String[]) - Method in class hex.svd.SVDModel
 
makeMetricBuilder(String[]) - Method in class hex.tree.SharedTreeModel
 
makeMetricBuilder(String[]) - Method in class hex.word2vec.Word2VecModel
 
makeModel(Key, P, double, double) - Method in class hex.tree.SharedTree.Driver
 
makeModelMetrics(Model, Frame, double) - Method in class hex.glm.GLMValidation
 
makeModelMetrics(Model, Frame, double) - Method in class hex.glrm.GLRMModel.ModelMetricsGLRM.GLRMModelMetrics
 
makeModelMetrics(Model, Frame, double) - Method in class hex.svd.SVDModel.ModelMetricsSVD.SVDModelMetrics
 
makeNeuronsForTesting(DeepLearningModel.DeepLearningModelInfo) - Static method in class hex.deeplearning.DeepLearningTask
 
makeNeuronsForTraining(DeepLearningModel.DeepLearningModelInfo) - Static method in class hex.deeplearning.DeepLearningTask
 
makeUndecidedNode(DHistogram[]) - Method in class hex.tree.DTree.DecidedNode
 
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.glm.GLMTask.GLMCoordinateDescentTask
 
map(Chunk[]) - Method in class hex.glm.GLMTask.GLMIterationTask
 
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.gbm.ResidualsCollector
 
map(Chunk[]) - Method in class hex.tree.Score
 
map(Chunk[]) - Method in class hex.tree.ScoreBuildHistogram
 
map(Chunk[]) - Method in class hex.word2vec.WordCountTask
Iterates over all chunks containing strings, and adds unique instances of those strings to a node local hashmap.
map(Chunk[]) - Method in class hex.word2vec.WordVectorTrainer
 
mapNames(String[]) - Method in class hex.DataInfo
 
matches - Variable in class hex.schemas.GrepModelV3.GrepModelOutputV3
 
max_active_predictors - Variable in class hex.schemas.GLMV3.GLMParametersV3
 
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.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.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.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.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.SharedTreeV3.SharedTreeParametersV3
 
max_depth - Variable in class hex.schemas.TreeStatsV3
 
max_hit_ratio_k - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
The maximum number (top K) of predictions to use for hit ratio computation (for multi-class only, 0 to disable)
max_hit_ratio_k - Variable in class hex.schemas.GLMV3.GLMParametersV3
The maximum number (top K) of predictions to use for hit ratio computation (for multi-class only, 0 to disable)
max_hit_ratio_k - Variable in class hex.schemas.NaiveBayesV3.NaiveBayesParametersV3
The maximum number (top K) of predictions to use for hit ratio computation (for multi-class only, 0 to disable)
max_hit_ratio_k - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3
The maximum number (top K) of predictions to use for hit ratio computation (for multi-class only, 0 to disable)
max_iterations - Variable in class hex.schemas.ExampleV3.ExampleParametersV3
 
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.PCAV3.PCAParametersV3
 
max_iterations - Variable in class hex.schemas.SVDV3.SVDParametersV3
 
max_leaves - Variable in class hex.schemas.TreeStatsV3
 
max_w2 - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
A maximum on the sum of the squared incoming weights into any one neuron.
maxIter() - Method in class hex.optimization.L_BFGS
 
maxs - Variable in class hex.schemas.ExampleModelV3.ExampleModelOutputV3
 
mean(int) - Method in class hex.tree.DBinomHistogram
 
mean(int) - Method in class hex.tree.DHistogram
 
mean(int) - Method in class hex.tree.DRealHistogram
 
mean_a - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningModelInfo
 
mean_depth - Variable in class hex.schemas.TreeStatsV3
 
mean_leaves - Variable in class hex.schemas.TreeStatsV3
 
mid(int, float, int) - Method in class hex.tree.TreeVisitor
 
min_depth - Variable in class hex.schemas.TreeStatsV3
 
min_leaves - Variable in class hex.schemas.TreeStatsV3
 
min_prob - Variable in class hex.schemas.NaiveBayesV3.NaiveBayesParametersV3
 
min_rows - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3
 
min_sdev - Variable in class hex.schemas.NaiveBayesV3.NaiveBayesParametersV3
 
min_step_size - Variable in class hex.schemas.GLRMV3.GLRMParametersV3
 
minWordFreq - Variable in class hex.schemas.Word2VecV3.Word2VecParametersV3
 
missing_int_value - Static variable in class hex.deeplearning.Neurons
 
missing_real_value - Static variable in class hex.deeplearning.Neurons
 
missing_values_handling - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
 
missingColumnsType() - Method in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
 
mlgrad(double[], int) - Method in class hex.glrm.GLRMModel.GLRMParameters
 
mloss(double[], int) - Method in class hex.glrm.GLRMModel.GLRMParameters
 
model - Variable in class hex.schemas.MakeGLMModelV3
 
model_info() - Method in class hex.deeplearning.DeepLearningModel
 
model_info() - Method in class hex.deeplearning.DeepLearningTask
 
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_NAME - Static variable in class hex.kmeans.KMeansGrid
 
MODEL_NAME - Static variable in class hex.tree.drf.DRFGrid
 
MODEL_NAME - Static variable in class hex.tree.gbm.GBMGrid
 
MODEL_NAME - Static variable in class hex.tree.SharedTreeGrid
 
ModelMetricsSVDV3 - Class in water.api
 
ModelMetricsSVDV3() - Constructor for class water.api.ModelMetricsSVDV3
 
modelName() - Method in class hex.kmeans.KMeansGrid
 
modelName() - Method in class hex.tree.drf.DRFGrid
 
modelName() - Method in class hex.tree.gbm.GBMGrid
 
modelName() - Method in class hex.tree.SharedTreeGrid
 
modifyParms(DeepLearningModel.DeepLearningParameters, DeepLearningModel.DeepLearningParameters, boolean) - Static method in class hex.deeplearning.DeepLearningModel
Take user-given parameters and turn them into usable, fully populated parameters (e.g., to be used by Neurons during training)
momentum() - Method in class hex.deeplearning.Neurons
 
momentum(long) - 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.
mse() - Method in class hex.deeplearning.DeepLearningModel
 
mtries - Variable in class hex.schemas.DRFV3.DRFParametersV3
 
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
 
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

n - Variable in class hex.coxph.CoxPH.CoxPHTask
 
n_missing - Variable in class hex.coxph.CoxPH.CoxPHTask
 
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
 
NaiveBayesBuilderHandler - Class in hex.api
 
NaiveBayesBuilderHandler() - Constructor for class hex.api.NaiveBayesBuilderHandler
 
NaiveBayesModel - Class in hex.naivebayes
 
NaiveBayesModel(Key, NaiveBayesModel.NaiveBayesParameters, NaiveBayesModel.NaiveBayesOutput) - Constructor for class hex.naivebayes.NaiveBayesModel
 
NaiveBayesModel.NaiveBayesOutput - Class in hex.naivebayes
 
NaiveBayesModel.NaiveBayesOutput(NaiveBayes) - Constructor for class hex.naivebayes.NaiveBayesModel.NaiveBayesOutput
 
NaiveBayesModel.NaiveBayesParameters - Class in hex.naivebayes
 
NaiveBayesModel.NaiveBayesParameters() - Constructor for class hex.naivebayes.NaiveBayesModel.NaiveBayesParameters
 
NaiveBayesModelV3 - Class in hex.schemas
 
NaiveBayesModelV3() - Constructor for class hex.schemas.NaiveBayesModelV3
 
NaiveBayesModelV3.NaiveBayesModelOutputV3 - Class in hex.schemas
 
NaiveBayesModelV3.NaiveBayesModelOutputV3() - Constructor for class hex.schemas.NaiveBayesModelV3.NaiveBayesModelOutputV3
 
NaiveBayesV3 - Class in hex.schemas
 
NaiveBayesV3() - Constructor for class hex.schemas.NaiveBayesV3
 
NaiveBayesV3.NaiveBayesParametersV3 - Class in hex.schemas
 
NaiveBayesV3.NaiveBayesParametersV3() - Constructor for class hex.schemas.NaiveBayesV3.NaiveBayesParametersV3
 
names() - Method in class hex.glm.GLMModel
 
names - Variable in class hex.schemas.MakeGLMModelV3
 
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
 
nclasses() - Method in class hex.glm.GLMModel.GLMOutput
 
negSampleCnt - Variable in class hex.schemas.Word2VecV3.Word2VecParametersV3
 
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.DenseColMatrix - Class in hex.deeplearning
Dense column matrix implementation
Neurons.DenseRowMatrix - Class in hex.deeplearning
Dense row matrix implementation
Neurons.DenseVector - Class in hex.deeplearning
Dense vector implementation
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.Linear(int) - Constructor for class hex.deeplearning.Neurons.Linear
 
Neurons.Matrix - Interface in hex.deeplearning
Abstract matrix interface
Neurons.Maxout - Class in hex.deeplearning
Maxout neurons
Neurons.Maxout(int) - Constructor for class hex.deeplearning.Neurons.Maxout
 
Neurons.MaxoutDropout - Class in hex.deeplearning
Maxout neurons with dropout
Neurons.MaxoutDropout(int) - Constructor for class hex.deeplearning.Neurons.MaxoutDropout
 
Neurons.Output - Class in hex.deeplearning
Abstract class for Output neurons
Neurons.Rectifier - Class in hex.deeplearning
Rectifier linear unit (ReLU) neurons
Neurons.Rectifier(int) - Constructor for class hex.deeplearning.Neurons.Rectifier
 
Neurons.RectifierDropout - Class in hex.deeplearning
Rectifier linear unit (ReLU) neurons with dropout
Neurons.RectifierDropout(int) - Constructor for class hex.deeplearning.Neurons.RectifierDropout
 
Neurons.Softmax - Class in hex.deeplearning
Output neurons for classification - Softmax
Neurons.Softmax(int) - Constructor for class hex.deeplearning.Neurons.Softmax
 
Neurons.SparseRowMatrix - Class in hex.deeplearning
Sparse row matrix implementation
Neurons.SparseVector - Class in hex.deeplearning
Sparse vector implementation
Neurons.SparseVector.Iterator - Class in hex.deeplearning
Iterator over a sparse vector
Neurons.Tanh - Class in hex.deeplearning
Tanh neurons - most common, most stable
Neurons.Tanh(int) - Constructor for class hex.deeplearning.Neurons.Tanh
 
Neurons.TanhDropout - Class in hex.deeplearning
Tanh neurons with dropout
Neurons.TanhDropout(int) - Constructor for class hex.deeplearning.Neurons.TanhDropout
 
Neurons.Vector - Interface in hex.deeplearning
Abstract vector interface
newDenseRow() - Method in class hex.DataInfo
 
nfeatures() - Method in class hex.deeplearning.DeepLearningModel.DeepLearningModelOutput
 
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.
nid() - Method in class hex.tree.DTree.Node
 
nid2Oob(int) - Static method in class hex.tree.ScoreBuildHistogram
 
nlambdas - Variable in class hex.schemas.GLMV3.GLMParametersV3
 
nNums - Variable in class hex.DataInfo.Row
 
nnz() - Method in class hex.deeplearning.Neurons.SparseVector
 
node(int) - Method in class hex.tree.DTree
 
non_negative - Variable in class hex.schemas.GLMV3.GLMParametersV3
 
normModel - Variable in class hex.schemas.Word2VecV3.Word2VecParametersV3
 
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.
ns(Chunk[], int) - Method in class hex.tree.DTree.DecidedNode
 
ntrees - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3
 
ntrees() - Method in class hex.tree.DTreeScorer
 
nullDeviance() - Method in class hex.glm.GLMValidation
 
nullDOF() - Method in class hex.glm.GLMValidation
 
numIds - Variable in class hex.DataInfo.Row
 
numStart() - Method in class hex.DataInfo
 
numVals - Variable in class hex.DataInfo.Row
 
nv - Variable in class hex.schemas.SVDV3.SVDParametersV3
 

O

objective - Variable in class hex.schemas.GLRMModelV3.GLRMModelOutputV3
 
objective_epsilon - Variable in class hex.schemas.GLMV3.GLMParametersV3
 
objVal - Variable in class hex.optimization.L_BFGS.LineSearchSol
 
offset - Variable in class hex.DataInfo.Row
 
offset_column - Variable in class hex.schemas.GLMV3.GLMParametersV3
 
offset_columns - Variable in class hex.coxph.CoxPHModel.CoxPHParameters
 
offsetChunkId() - Method in class hex.DataInfo
 
offsets - Variable in class hex.schemas.GrepModelV3.GrepModelOutputV3
 
onCompletion(CountedCompleter) - Method in class hex.glm.GLM.GLMDriver
 
onCompletion(CountedCompleter) - Method in class hex.gram.Gram.Cholesky.ParSolver
 
onExceptionalCompletion(Throwable, CountedCompleter) - Method in class hex.glm.GLM.GLMDriver
 
oob2Nid(int) - Static method in class hex.tree.ScoreBuildHistogram
 
OUT_OF_BAG - Static variable in class hex.tree.ScoreBuildHistogram
Marker for sampled out rows
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.CoxPHV3.CoxPHParametersV3
 
own_fields - Static variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
 
own_fields - Static variable in class hex.schemas.DRFV3.DRFParametersV3
 
own_fields - Static variable in class hex.schemas.ExampleV3.ExampleParametersV3
 
own_fields - Static variable in class hex.schemas.GBMV3.GBMParametersV3
 
own_fields - Static variable in class hex.schemas.GLMV3.GLMParametersV3
 
own_fields - Static variable in class hex.schemas.GLRMV3.GLRMParametersV3
 
own_fields - Static variable in class hex.schemas.GrepV3.GrepParametersV3
 
own_fields - Static variable in class hex.schemas.KMeansV3.KMeansParametersV3
 
own_fields - Static variable in class hex.schemas.NaiveBayesV3.NaiveBayesParametersV3
 
own_fields - Static variable in class hex.schemas.PCAV3.PCAParametersV3
 
own_fields - Static variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3
 
own_fields - Static variable in class hex.schemas.SVDV3.SVDParametersV3
 
own_fields - Static variable in class hex.schemas.Word2VecV3.Word2VecParametersV3
 

P

parameters - Variable in class hex.GridSearchSchema
 
params - Variable in class hex.deeplearning.Neurons
Parameters (deep-cloned() from the user input, can be modified here, e.g.
parseJsonMap(String, T) - Static method in class hex.GridSearchSchema
 
parSolver(CountedCompleter, double[], int, int) - Method in class hex.gram.Gram.Cholesky
 
pc_importance - Variable in class hex.schemas.GLRMModelV3.GLRMModelOutputV3
 
pc_importance - Variable in class hex.schemas.PCAModelV3.PCAModelOutputV3
 
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.EmbeddedSVD - Class in hex.pca
 
PCA.EmbeddedSVD(SVDModel.SVDParameters, Key) - Constructor for class hex.pca.PCA.EmbeddedSVD
 
PCA.Initialization - Enum in hex.pca
 
PCABuilderHandler - Class in hex.api
 
PCABuilderHandler() - Constructor for class hex.api.PCABuilderHandler
 
PCAModel - Class in hex.pca
 
PCAModel(Key, PCAModel.PCAParameters, PCAModel.PCAOutput) - Constructor for class hex.pca.PCAModel
 
PCAModel.PCAOutput - Class in hex.pca
 
PCAModel.PCAOutput(PCA) - Constructor for class hex.pca.PCAModel.PCAOutput
 
PCAModel.PCAParameters - Class in hex.pca
 
PCAModel.PCAParameters() - Constructor for class hex.pca.PCAModel.PCAParameters
 
PCAModelV3 - Class in hex.schemas
 
PCAModelV3() - Constructor for class hex.schemas.PCAModelV3
 
PCAModelV3.PCAModelOutputV3 - Class in hex.schemas
 
PCAModelV3.PCAModelOutputV3() - Constructor for class hex.schemas.PCAModelV3.PCAModelOutputV3
 
PCAV3 - Class in hex.schemas
 
PCAV3() - Constructor for class hex.schemas.PCAV3
 
PCAV3.PCAParametersV3 - Class in hex.schemas
 
PCAV3.PCAParametersV3() - Constructor for class hex.schemas.PCAV3.PCAParametersV3
 
pcond - Variable in class hex.schemas.NaiveBayesModelV3.NaiveBayesModelOutputV3
 
perRow(double[], float[], Model) - Method in class hex.glm.GLMValidation
 
perRow(double[], float[], double, double, Model) - Method in class hex.glm.GLMValidation
 
perRow(double[], float[], Model) - Method in class hex.glrm.GLRMModel.ModelMetricsGLRM.GLRMModelMetrics
 
perRow(double[], float[], Model) - Method in class hex.svd.SVDModel.ModelMetricsSVD.SVDModelMetrics
 
pickBestModel() - Method in class hex.glm.GLMModel.GLMOutput
 
pid() - Method in class hex.tree.DTree.Node
 
post(int, float, int) - Method in class hex.tree.TreeVisitor
 
postGlobal() - Method in class hex.coxph.CoxPH.CoxPHTask
 
postGlobal() - Method in class hex.deeplearning.DeepLearningTask
 
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.glm.GLMTask.GLMIterationTask
 
postGlobal() - Method in class hex.word2vec.WordCountTask
Once hashmap has been consolidated to single node, filter out infrequent words, then sort array according to frequency (descending), finally put the results into a frame.
postGlobal() - Method in class hex.word2vec.WordVectorTrainer
 
powerLoop(double[][]) - Method in class hex.svd.SVD
 
powerLoop(double[][], long) - Method in class hex.svd.SVD
 
powerLoop(double[][], double[]) - Method in class hex.svd.SVD
 
pre(int, float, IcedBitSet, int) - Method in class hex.tree.TreeVisitor
 
pre_split_se() - Method in class hex.tree.DTree.Split
 
pred(int) - Method in class hex.tree.DTree.DecidedNode
 
pred() - Method in class hex.tree.DTree.LeafNode
 
printGenerateTrees(DTree[]) - Static method in class hex.tree.SharedTree
 
prior - Variable in class hex.schemas.GLMV3.GLMParametersV3
 
processRow(long, DataInfo.Row) - Method in class hex.coxph.CoxPH.CoxPHTask
 
processRow(long, DataInfo.Row) - Method in class hex.deeplearning.DeepLearningTask
 
processRow(long, DataInfo.Row) - Method in class hex.FrameTask
Method to process one row of the data for GLM functions.
processRow(long, DataInfo.Row, NewChunk[]) - Method in class hex.FrameTask
 
processRow(DataInfo.Row) - Method in class hex.glm.GLMTask.GLMIterationTask
 
processRow(long, DataInfo.Row) - Method in class hex.gram.Gram.GramTask
 
progress(double[], L_BFGS.GradientInfo) - Method in class hex.optimization.L_BFGS.ProgressMonitor
 

Q

QuantileBuilderHandler - Class in hex.api
 
QuantileBuilderHandler() - Constructor for class hex.api.QuantileBuilderHandler
 
quiet_mode - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
Enable quiet mode for less output to standard output.

R

r2_stopping - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3
 
randomlySparsifyActivation(Neurons.Vector, long) - Method in class hex.deeplearning.Dropout
 
rank() - Method in class hex.glm.GLMModel.GLMOutput
 
rank() - Method in class hex.glm.GLMModel.Submodel
 
rate(long) - Method in class hex.deeplearning.Neurons
The learning rate
rate - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
When adaptive learning rate is disabled, the magnitude of the weight updates are determined by the user specified learning rate (potentially annealed), and are a function of the difference between the predicted value and the target value.
rate_annealing - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
Learning rate annealing reduces the learning rate to "freeze" into local minima in the optimization landscape.
rate_decay - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
The learning rate decay parameter controls the change of learning rate across layers.
raw() - Method in class hex.deeplearning.Neurons.DenseColMatrix
 
raw() - Method in class hex.deeplearning.Neurons.DenseRowMatrix
 
raw() - Method in class hex.deeplearning.Neurons.DenseVector
 
raw() - Method in interface hex.deeplearning.Neurons.Matrix
 
raw() - Method in class hex.deeplearning.Neurons.SparseRowMatrix
 
raw() - Method in class hex.deeplearning.Neurons.SparseVector
 
raw() - Method in interface hex.deeplearning.Neurons.Vector
 
rcumsumRisk - Variable in class hex.coxph.CoxPH.CoxPHTask
 
rcumsumXRisk - Variable in class hex.coxph.CoxPH.CoxPHTask
 
rcumsumXXRisk - Variable in class hex.coxph.CoxPH.CoxPHTask
 
read_impl(AutoBuffer) - Method in class hex.word2vec.WordCountTask
Automagically called as a node receives results from another node to be reduced.
recover_pca - Variable in class hex.schemas.GLRMV3.GLRMParametersV3
 
reduce(CoxPH.CoxPHTask) - Method in class hex.coxph.CoxPH.CoxPHTask
 
reduce(DeepLearningTask) - Method in class hex.deeplearning.DeepLearningTask
 
reduce(DeepLearningTask2) - Method in class hex.deeplearning.DeepLearningTask2
Reduce between worker nodes, with network traffic (if greater than 1 nodes) After all reduce()'s are done, postGlobal() will be called
reduce(GLMTask.GLMCoordinateDescentTask) - Method in class hex.glm.GLMTask.GLMCoordinateDescentTask
 
reduce(GLMTask.GLMIterationTask) - Method in class hex.glm.GLMTask.GLMIterationTask
 
reduce(GLMValidation) - Method in class hex.glm.GLMValidation
 
reduce(Gram.GramTask) - Method in class hex.gram.Gram.GramTask
 
reduce(TreeMeasuresCollector) - Method in class hex.tree.drf.TreeMeasuresCollector
 
reduce(Score) - Method in class hex.tree.Score
 
reduce(ScoreBuildHistogram) - Method in class hex.tree.ScoreBuildHistogram
 
reduce(WordCountTask) - Method in class hex.word2vec.WordCountTask
Local reduces should all see same HM.
reduce(WordVectorTrainer) - Method in class hex.word2vec.WordVectorTrainer
 
regex - Variable in class hex.schemas.GrepV3.GrepParametersV3
 
regression_stop - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
The stopping criteria in terms of regression error (MSE) on the training data scoring dataset.
regularization_x - Variable in class hex.schemas.GLRMV3.GLRMParametersV3
 
regularization_y - Variable in class hex.schemas.GLRMV3.GLRMParametersV3
 
regularize(double, GLRMModel.GLRMParameters.Regularizer) - Method in class hex.glrm.GLRMModel.GLRMParameters
 
regularize(double[][], GLRMModel.GLRMParameters.Regularizer) - Method in class hex.glrm.GLRMModel.GLRMParameters
 
regularize_x(double) - Method in class hex.glrm.GLRMModel.GLRMParameters
 
regularize_x(double[][]) - Method in class hex.glrm.GLRMModel.GLRMParameters
 
regularize_y(double) - Method in class hex.glrm.GLRMModel.GLRMParameters
 
regularize_y(double[][]) - Method in class hex.glrm.GLRMModel.GLRMParameters
 
remove_impl(Futures) - Method in class hex.tree.SharedTreeModel
 
replicate_training_data - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
Replicate the entire training dataset onto every node for faster training on small datasets.
reproducible - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
 
resDOF() - Method in class hex.glm.GLMValidation
 
residualDeviance() - Method in class hex.glm.GLMValidation
 
ResidualsCollector - Class in hex.tree.gbm
 
ResidualsCollector(int, int, Key[][]) - Constructor for class hex.tree.gbm.ResidualsCollector
 
response - Variable in class hex.DataInfo.Row
 
response(int) - Method in class hex.DataInfo.Row
 
response() - Method in class hex.tree.SharedTree
 
response_column - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
 
response_column - Variable in class hex.schemas.GLMV3.GLMParametersV3
 
response_column - Variable in class hex.schemas.NaiveBayesV3.NaiveBayesParametersV3
 
response_column - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3
 
responseChunkId() - Method in class hex.DataInfo
 
resultSSE() - Method in class hex.tree.drf.TreeMeasuresCollector
 
resultVotes() - Method in class hex.tree.drf.TreeMeasuresCollector
 
rho() - Method in class hex.glm.GLM.GramSolver
 
rho() - Method in class hex.glm.GLM.LBFGS_ProximalSolver
 
rho() - Method in interface hex.optimization.ADMM.ProximalSolver
 
rho - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
The first of two hyper parameters for adaptive learning rate (ADADELTA).
rid - Variable in class hex.DataInfo.Row
 
rms_weight - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningModelInfo
 
rngForChunk(int) - Method in class hex.tree.CompressedTree
 
root() - Method in class hex.tree.DTree
 
rows() - Method in class hex.deeplearning.Neurons.DenseColMatrix
 
rows() - Method in class hex.deeplearning.Neurons.DenseRowMatrix
 
rows() - Method in interface hex.deeplearning.Neurons.Matrix
 
rows() - Method in class hex.deeplearning.Neurons.SparseRowMatrix
 
rproxgrad(double, double, double, GLRMModel.GLRMParameters.Regularizer) - Method in class hex.glrm.GLRMModel.GLRMParameters
 
rproxgrad_x(double, double) - Method in class hex.glrm.GLRMModel.GLRMParameters
 
rproxgrad_y(double, double) - Method in class hex.glrm.GLRMModel.GLRMParameters
 
run_time - Variable in class hex.deeplearning.DeepLearningModel
 

S

sample_rate - Variable in class hex.schemas.DRFV3.DRFParametersV3
 
schema() - Method in class hex.coxph.CoxPH
 
schema() - Method in class hex.coxph.CoxPHModel
 
schema() - Method in class hex.deeplearning.DeepLearning
 
schema() - Method in class hex.deeplearning.DeepLearningModel
 
schema() - Method in class hex.example.Example
 
schema() - Method in class hex.glm.GLM
 
schema() - Method in class hex.glrm.GLRM
 
schema() - Method in class hex.grep.Grep
 
schema() - Method in class hex.kmeans.KMeans
 
schema() - Method in class hex.naivebayes.NaiveBayes
 
schema() - Method in class hex.naivebayes.NaiveBayesModel
 
schema() - Method in class hex.pca.PCA
 
schema() - Method in class hex.svd.SVD
 
schema() - Method in class hex.tree.drf.DRF
 
schema() - Method in class hex.tree.gbm.GBM
 
schema() - Method in class hex.word2vec.Word2Vec
 
score(Frame, String) - Method in class hex.deeplearning.DeepLearningModel
 
score(Frame, String) - Method in class hex.pca.PCAModel
 
score(Frame, String) - Method in class hex.svd.SVDModel
 
score(double[]) - Method in class hex.tree.CompressedTree
Highly efficient (critical path) tree scoring
Score - Class in hex.tree
Score the tree columns, and produce a confusion matrix and AUC
Score(SharedTree, boolean, boolean, ModelCategory) - Constructor for class hex.tree.Score
Compute ModelMetrics on the testing dataset.
score0(double[], double[]) - Method in class hex.coxph.CoxPHModel
Predict from raw double values representing the data
score0(double[], double[]) - Method in class hex.deeplearning.DeepLearningModel
Predict from raw double values representing the data
score0(double[], double[]) - Method in class hex.example.ExampleModel
 
score0(Chunk[], int, double[], double[]) - Method in class hex.glm.GLMModel
 
score0(double[], double[]) - Method in class hex.glm.GLMModel
 
score0(double[], double[], double, double) - Method in class hex.glm.GLMModel
 
score0(double[], double[]) - Method in class hex.glrm.GLRMModel
 
score0(double[], double[]) - Method in class hex.grep.GrepModel
 
score0(double[], double[]) - Method in class hex.kmeans.KMeansModel
 
score0(double[], double[]) - Method in class hex.naivebayes.NaiveBayesModel
 
score0(double[], double[]) - Method in class hex.pca.PCAModel
 
score0(double[], double[]) - Method in class hex.svd.SVDModel
 
score0(Chunk[], int, double[], double[]) - Method in class hex.tree.drf.DRFModel
Bulk scoring API for one row.
score0(double[], double[]) - Method in class hex.tree.drf.DRFModel
 
score0(double[], double[], CompressedTree[]) - Method in class hex.tree.DTreeScorer
 
score0(Chunk[], int, double[], double[]) - Method in class hex.tree.gbm.GBMModel
Bulk scoring API for one row.
score0(double[], double[]) - Method in class hex.tree.gbm.GBMModel
 
score0(double[], double[]) - Method in class hex.tree.SharedTreeModel
 
score0(double[], double[], int) - Method in class hex.tree.SharedTreeModel
 
score0(Chunk[], int, double[], double[]) - Method in class hex.word2vec.Word2VecModel
 
score0(double[], double[]) - Method in class hex.word2vec.Word2VecModel
 
score1(Chunk[], double[], int) - Method in class hex.tree.drf.DRF
 
score1(Chunk[], double[], int) - Method in class hex.tree.gbm.GBM
 
score1(Chunk[], double[], int) - Method in class hex.tree.SharedTree
 
score_duty_cycle - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
Maximum fraction of wall clock time spent on model scoring on training and validation samples, and on diagnostics such as computation of feature importances (i.e., not on training).
score_interval - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
The minimum time (in seconds) to elapse between model scoring.
score_training_samples - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningScoring
 
score_training_samples - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
The number of training dataset points to be used for scoring.
score_validation_samples - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningScoring
 
score_validation_samples - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
The number of validation dataset points to be used for scoring.
score_validation_sampling - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
Method used to sample the validation dataset for scoring, see Score Validation Samples above.
scoreAutoEncoder(Frame, Key) - Method in class hex.deeplearning.DeepLearningModel
Score auto-encoded reconstruction (on-the-fly, without allocating the reconstruction as done in Frame score(Frame fr))
ScoreBuildHistogram - Class in hex.tree
Score and Build Histogram
ScoreBuildHistogram(H2O.H2OCountedCompleter, int, int, int, int, DTree, int, DHistogram[][], boolean) - Constructor for class hex.tree.ScoreBuildHistogram
 
scoreCols(DHistogram[]) - Method in class hex.tree.DTree.UndecidedNode
 
scoreDeepFeatures(Frame, int) - Method in class hex.deeplearning.DeepLearningModel
Score auto-encoded reconstruction (on-the-fly, and materialize the deep features of given layer
scoreImpl(Frame, Frame, String) - Method in class hex.deeplearning.DeepLearningModel
Make either a prediction or a reconstruction.
scoreImpl(Frame, Frame, String) - Method in class hex.pca.PCAModel
 
scoreImpl(Frame, Frame, String) - Method in class hex.svd.SVDModel
 
scoreMSE(int, int) - Method in class hex.tree.DBinomHistogram
 
scoreMSE(int, int) - Method in class hex.tree.DHistogram
 
scoreMSE(int, int) - Method in class hex.tree.DRealHistogram
 
scoreTree(double[], double[], CompressedTree[]) - Static method in class hex.tree.DTreeScorer
Score given tree on the row of data.
scoring_history() - Method in class hex.deeplearning.DeepLearningModel
 
scoring_time - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningScoring
 
se() - Method in class hex.tree.DTree.Split
 
seed - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
The random seed controls sampling and initialization.
seed - Variable in class hex.schemas.GLRMV3.GLRMParametersV3
 
seed - Variable in class hex.schemas.KMeansV3.KMeansParametersV3
 
seed - Variable in class hex.schemas.PCAV3.PCAParametersV3
 
seed - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3
 
seed - Variable in class hex.schemas.SVDV3.SVDParametersV3
 
seed(int) - Static method in class hex.tree.drf.TreeMeasuresCollector.ShuffleTask
 
sentSampleRate - Variable in class hex.schemas.Word2VecV3.Word2VecParametersV3
 
set(int, int, float) - Method in class hex.deeplearning.Neurons.DenseColMatrix
 
set(int, int, float) - Method in class hex.deeplearning.Neurons.DenseRowMatrix
 
set(int, float) - Method in class hex.deeplearning.Neurons.DenseVector
 
set(int, int, float) - Method in interface hex.deeplearning.Neurons.Matrix
 
set(int, int, float) - Method in class hex.deeplearning.Neurons.SparseRowMatrix
 
set(int, float) - Method in class hex.deeplearning.Neurons.SparseVector
 
set(int, float) - Method in interface hex.deeplearning.Neurons.Vector
 
set(byte[], int, int, long) - Method in class hex.word2vec.WordCountTask.ValueStringCount
 
set_processed_global(long) - Method in class hex.deeplearning.DeepLearningModel.DeepLearningModelInfo
 
set_processed_local(long) - Method in class hex.deeplearning.DeepLearningModel.DeepLearningModelInfo
 
set_unstable() - Method in class hex.deeplearning.DeepLearningModel.DeepLearningModelInfo
 
setBetaStart(double[]) - Method in class hex.glm.GLM.BetaConstraint
 
setBetaStart(double[]) - Method in class hex.glm.GLM.GLMGradientSolver
 
setGradEps(double) - Method in class hex.glm.GLM.LBFGS_ProximalSolver
 
setGradEps(double) - Method in class hex.optimization.L_BFGS
 
setGradientNorm(MathUtils.Norm) - Method in class hex.optimization.ADMM.L1Solver
 
setHistorySz(int) - Method in class hex.optimization.L_BFGS
 
setInput(long, double[]) - Method in class hex.deeplearning.Neurons.Input
One of two methods to set layer input values.
setInput(long, double[], int, int[]) - Method in class hex.deeplearning.Neurons.Input
The second method used to set input layer values.
setLocallyProcessed(int) - Method in class hex.word2vec.Word2VecModel.Word2VecModelInfo
 
setLowerBounds(double[]) - Method in class hex.glm.GLM.BetaConstraint
 
setMax(float) - Method in class hex.tree.DHistogram
 
setMaxIter(int) - Method in class hex.optimization.L_BFGS
 
setMin(float) - Method in class hex.tree.DHistogram
 
setMinIter(int) - Method in class hex.optimization.L_BFGS
 
setModelBuilderTrain(Frame) - Method in class hex.coxph.CoxPH.CoxPHDriver
 
setNumTrees(int) - Method in class hex.tree.TreeStats
 
setObjEps(double) - Method in class hex.glm.GLM.LBFGS_ProximalSolver
 
setObjEps(double) - Method in class hex.optimization.L_BFGS
 
setPredictorTransform(DataInfo.TransformType) - Method in class hex.DataInfo
 
setProximalPenalty(double[], double[]) - Method in class hex.glm.GLM.BetaConstraint
 
setResponseTransform(DataInfo.TransformType) - Method in class hex.DataInfo
 
setSparse(boolean) - Method in class hex.glm.GLMTask.GLMIterationTask
 
setSPD(boolean) - Method in class hex.gram.Gram.Cholesky
 
setSubmodel(GLMModel.Submodel) - Method in class hex.glm.GLMModel
 
setSubmodelIdx(int) - Method in class hex.glm.GLMModel.GLMOutput
 
setupLocal() - Method in class hex.deeplearning.DeepLearningTask
 
setupLocal() - Method in class hex.deeplearning.DeepLearningTask2
Do the local computation: Perform one DeepLearningTask (with run_local=true) iteration.
setupLocal() - Method in class hex.FrameTask
 
setupLocal() - Method in class hex.tree.DTreeScorer
 
setupLocal() - Method in class hex.tree.ScoreBuildHistogram
 
setupLocal() - Method in class hex.word2vec.WordCountTask
 
setupLocal() - Method in class hex.word2vec.WordVectorTrainer
 
setUpperBounds(double[]) - Method in class hex.glm.GLM.BetaConstraint
 
SharedTree<M extends SharedTreeModel<M,P,O>,P extends SharedTreeModel.SharedTreeParameters,O extends SharedTreeModel.SharedTreeOutput> - Class in hex.tree
 
SharedTree(String, P) - Constructor for class hex.tree.SharedTree
 
SharedTree.Driver - Class in hex.tree
 
SharedTree.Driver() - Constructor for class hex.tree.SharedTree.Driver
 
SharedTreeGrid<P extends SharedTreeModel.SharedTreeParameters,G extends SharedTreeGrid<P,G>> - Class in hex.tree
A Grid of Models Used to explore Model hyper-parameter space.
SharedTreeGrid(Key, Frame) - Constructor for class hex.tree.SharedTreeGrid
 
SharedTreeModel<M extends SharedTreeModel<M,P,O>,P extends SharedTreeModel.SharedTreeParameters,O extends SharedTreeModel.SharedTreeOutput> - Class in hex.tree
 
SharedTreeModel(Key, P, O) - Constructor for class hex.tree.SharedTreeModel
 
SharedTreeModel.SharedTreeOutput - Class in hex.tree
 
SharedTreeModel.SharedTreeOutput(SharedTree, double, double) - Constructor for class hex.tree.SharedTreeModel.SharedTreeOutput
 
SharedTreeModel.SharedTreeParameters - Class in hex.tree
 
SharedTreeModel.SharedTreeParameters() - Constructor for class hex.tree.SharedTreeModel.SharedTreeParameters
 
SharedTreeModelV3<M extends SharedTreeModel<M,P,O>,S extends SharedTreeModelV3<M,S,P,PS,O,OS>,P extends SharedTreeModel.SharedTreeParameters,PS extends SharedTreeV3.SharedTreeParametersV3<P,PS>,O extends SharedTreeModel.SharedTreeOutput,OS extends SharedTreeModelV3.SharedTreeModelOutputV3<O,OS>> - Class in hex.schemas
 
SharedTreeModelV3() - Constructor for class hex.schemas.SharedTreeModelV3
 
SharedTreeModelV3.SharedTreeModelOutputV3<O extends SharedTreeModel.SharedTreeOutput,SO extends SharedTreeModelV3.SharedTreeModelOutputV3<O,SO>> - Class in hex.schemas
 
SharedTreeModelV3.SharedTreeModelOutputV3() - Constructor for class hex.schemas.SharedTreeModelV3.SharedTreeModelOutputV3
 
SharedTreeV3<B extends SharedTree,S extends SharedTreeV3<B,S,P>,P extends SharedTreeV3.SharedTreeParametersV3> - Class in hex.schemas
 
SharedTreeV3() - Constructor for class hex.schemas.SharedTreeV3
 
SharedTreeV3.SharedTreeParametersV3<P extends SharedTreeModel.SharedTreeParameters,S extends SharedTreeV3.SharedTreeParametersV3<P,S>> - Class in hex.schemas
 
SharedTreeV3.SharedTreeParametersV3() - Constructor for class hex.schemas.SharedTreeV3.SharedTreeParametersV3
 
shrinkage(double, double) - Static method in class hex.optimization.ADMM
 
shuffle(Vec) - Static method in class hex.tree.drf.TreeMeasuresCollector.ShuffleTask
 
shuffle_training_data - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
Enable shuffling of training data (on each node).
ShuffleSplitFrame - Class in hex.splitframe
Frame splitter function to divide given frame into multiple partitions based on given ratios.
ShuffleSplitFrame() - Constructor for class hex.splitframe.ShuffleSplitFrame
 
shuffleSplitFrame(Frame, Key[], double[], long) - Static method in class hex.splitframe.ShuffleSplitFrame
 
single_node_mode - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
Run on a single node for fine-tuning of model parameters.
size() - Method in class hex.deeplearning.DeepLearningModel.DeepLearningModelInfo
 
size() - Method in class hex.deeplearning.Neurons.DenseColMatrix
 
size() - Method in class hex.deeplearning.Neurons.DenseRowMatrix
 
size() - Method in class hex.deeplearning.Neurons.DenseVector
 
size() - Method in interface hex.deeplearning.Neurons.Matrix
 
size() - Method in class hex.deeplearning.Neurons.SparseRowMatrix
 
size() - Method in class hex.deeplearning.Neurons.SparseVector
 
size() - Method in interface hex.deeplearning.Neurons.Vector
 
size() - Method in class hex.tree.DTree.DecidedNode
 
size() - Method in class hex.tree.DTree.Node
 
size() - Method in class hex.tree.DTree.UndecidedNode
 
sizeCensored - Variable in class hex.coxph.CoxPH.CoxPHTask
 
sizeEvents - Variable in class hex.coxph.CoxPH.CoxPHTask
 
sizeRiskSet - Variable in class hex.coxph.CoxPH.CoxPHTask
 
solve(boolean) - Method in class hex.glm.GLM.GLMSingleLambdaTsk
 
solve(double[]) - Method in class hex.glm.GLM.GramSolver
 
solve(double[], double[]) - Method in class hex.glm.GLM.GramSolver
 
solve(double[], double[]) - Method in class hex.glm.GLM.LBFGS_ProximalSolver
 
solve(double[]) - Method in class hex.gram.Gram.Cholesky
Find solution to A*x = y.
solve(ADMM.ProximalSolver, double[], double) - Method in class hex.optimization.ADMM.L1Solver
 
solve(ADMM.ProximalSolver, double[], double, boolean, double[], double[]) - Method in class hex.optimization.ADMM.L1Solver
 
solve(double[], double[]) - Method in interface hex.optimization.ADMM.ProximalSolver
 
solve(L_BFGS.GradientSolver, double[]) - Method in class hex.optimization.L_BFGS
Solve the optimization problem defined by the user-supplied gradient function using L-BFGS algorithm.
solve(L_BFGS.GradientSolver, double[], L_BFGS.GradientInfo, L_BFGS.ProgressMonitor) - Method in class hex.optimization.L_BFGS
Solve the optimization problem defined by the user-supplied gradient function using L-BFGS algorithm.
solver - Variable in class hex.schemas.GLMV3.GLMParametersV3
 
sparse - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
 
sparseness() - Method in class hex.gram.Gram.Cholesky
 
sparseness() - Method in class hex.gram.Gram
 
sparsity_beta - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
 
split(int, char, char, int, DHistogram[], float) - Method in class hex.tree.DTree.Split
 
standardize - Variable in class hex.schemas.GLMV3.GLMParametersV3
 
standardize - Variable in class hex.schemas.KMeansV3.KMeansParametersV3
 
start_column - Variable in class hex.coxph.CoxPHModel.CoxPHParameters
 
startCoefs(int, long) - Static method in class hex.optimization.L_BFGS
 
std_deviation - Variable in class hex.schemas.GLRMModelV3.GLRMModelOutputV3
 
std_deviation - Variable in class hex.schemas.PCAModelV3.PCAModelOutputV3
 
step(long, Neurons[], DeepLearningModel.DeepLearningModelInfo, boolean, double[]) - Static method in class hex.deeplearning.DeepLearningTask
 
step - Variable in class hex.optimization.L_BFGS.LineSearchSol
 
step_size - Variable in class hex.schemas.GLRMModelV3.GLRMModelOutputV3
 
stop_column - Variable in class hex.coxph.CoxPHModel.CoxPHParameters
 
subgrad(double, double[], double[]) - Static method in class hex.optimization.ADMM
 
suggestedNextHyperValue(int, Model, double[]) - Method in class hex.kmeans.KMeansGrid
 
suggestedNextHyperValue(int, Model, double[]) - Method in class hex.tree.drf.DRFGrid
 
suggestedNextHyperValue(int, Model, double[]) - Method in class hex.tree.gbm.GBMGrid
 
sumLogRiskEvents - Variable in class hex.coxph.CoxPH.CoxPHTask
 
summaryTable - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningModelInfo
 
sumRiskEvents - Variable in class hex.coxph.CoxPH.CoxPHTask
 
sumWeightedCatX - Variable in class hex.coxph.CoxPH.CoxPHTask
 
sumWeightedNumX - Variable in class hex.coxph.CoxPH.CoxPHTask
 
sumWeights - Variable in class hex.coxph.CoxPH.CoxPHTask
 
sumXEvents - Variable in class hex.coxph.CoxPH.CoxPHTask
 
sumXRiskEvents - Variable in class hex.coxph.CoxPH.CoxPHTask
 
sumXXRiskEvents - Variable in class hex.coxph.CoxPH.CoxPHTask
 
SVD - Class in hex.svd
SVD(SVDModel.SVDParameters) - Constructor for class hex.svd.SVD
 
SVDBuilderHandler - Class in hex.api
 
SVDBuilderHandler() - Constructor for class hex.api.SVDBuilderHandler
 
SVDModel - Class in hex.svd
 
SVDModel(Key, SVDModel.SVDParameters, SVDModel.SVDOutput) - Constructor for class hex.svd.SVDModel
 
SVDModel.ModelMetricsSVD - Class in hex.svd
 
SVDModel.ModelMetricsSVD(Model, Frame) - Constructor for class hex.svd.SVDModel.ModelMetricsSVD
 
SVDModel.ModelMetricsSVD.SVDModelMetrics - Class in hex.svd
 
SVDModel.ModelMetricsSVD.SVDModelMetrics(int) - Constructor for class hex.svd.SVDModel.ModelMetricsSVD.SVDModelMetrics
 
SVDModel.SVDOutput - Class in hex.svd
 
SVDModel.SVDOutput(SVD) - Constructor for class hex.svd.SVDModel.SVDOutput
 
SVDModel.SVDParameters - Class in hex.svd
 
SVDModel.SVDParameters() - Constructor for class hex.svd.SVDModel.SVDParameters
 
SVDModelV3 - Class in hex.schemas
 
SVDModelV3() - Constructor for class hex.schemas.SVDModelV3
 
SVDModelV3.SVDModelOutputV3 - Class in hex.schemas
 
SVDModelV3.SVDModelOutputV3() - Constructor for class hex.schemas.SVDModelV3.SVDModelOutputV3
 
SVDV3 - Class in hex.schemas
 
SVDV3() - Constructor for class hex.schemas.SVDV3
 
SVDV3.SVDParametersV3 - Class in hex.schemas
 
SVDV3.SVDParametersV3() - Constructor for class hex.schemas.SVDV3.SVDParametersV3
 
synonyms - Variable in class hex.schemas.SynonymV3
 
SynonymV3 - Class in hex.schemas
 
SynonymV3() - Constructor for class hex.schemas.SynonymV3
 

T

target - Variable in class hex.schemas.SynonymV3
 
target_ratio_comm_to_comp - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
 
threshold - Variable in class hex.schemas.MakeGLMModelV3
 
ties - Variable in class hex.coxph.CoxPHModel.CoxPHParameters
 
time_for_communication_us - Variable in class hex.deeplearning.DeepLearningModel
 
toFrame(Key) - Method in class hex.deeplearning.Neurons.DenseColMatrix
 
toFrame(Key) - Method in class hex.deeplearning.Neurons.DenseRowMatrix
 
toFrame(Key) - Method in class hex.deeplearning.Neurons.DenseVector
 
toFrame(Key) - Method in interface hex.deeplearning.Neurons.Matrix
 
toFrame(Key) - Method in class hex.deeplearning.Neurons.SparseRowMatrix
 
toFrame(Key) - Method in class hex.deeplearning.Neurons.SparseVector
 
toFrame(Key) - Method in interface hex.deeplearning.Neurons.Vector
 
toJavaCheckTooBig() - Method in class hex.deeplearning.DeepLearningModel
 
toJavaCheckTooBig() - Method in class hex.glm.GLMModel
 
toJavaCheckTooBig() - Method in class hex.kmeans.KMeansModel
 
toJavaCheckTooBig() - Method in class hex.tree.SharedTreeModel
 
toJavaForestName(SB, String, int) - Method in class hex.tree.SharedTreeModel
 
toJavaInit(SB, SB) - Method in class hex.deeplearning.DeepLearningModel
 
toJavaInit(SB, SB) - Method in class hex.glm.GLMModel
 
toJavaInit(SB, SB) - Method in class hex.naivebayes.NaiveBayesModel
 
toJavaInit(SB, SB) - Method in class hex.pca.PCAModel
 
toJavaInit(SB, SB) - Method in class hex.tree.SharedTreeModel
 
toJavaPredictBody(SB, SB, SB) - Method in class hex.deeplearning.DeepLearningModel
 
toJavaPredictBody(SB, SB, SB) - Method in class hex.glm.GLMModel
 
toJavaPredictBody(SB, SB, SB) - Method in class hex.kmeans.KMeansModel
 
toJavaPredictBody(SB, SB, SB) - Method in class hex.naivebayes.NaiveBayesModel
 
toJavaPredictBody(SB, SB, SB) - Method in class hex.pca.PCAModel
 
toJavaPredictBody(SB, SB, SB) - Method in class hex.tree.SharedTreeModel
 
toJavaTreeName(SB, String, int, int) - Method in class hex.tree.SharedTreeModel
 
toJavaUnifyPreds(SB, SB) - Method in class hex.tree.drf.DRFModel
 
toJavaUnifyPreds(SB, SB) - Method in class hex.tree.gbm.GBMModel
 
toJavaUnifyPreds(SB, SB) - Method in class hex.tree.SharedTreeModel
 
toString() - Method in class hex.coxph.CoxPHModel
 
toString() - Method in class hex.DataInfo.Row
 
toString() - Method in class hex.deeplearning.DeepLearningModel.DeepLearningModelInfo
 
toString() - Method in class hex.deeplearning.DeepLearningModel.DeepLearningScoring
 
toString() - Method in class hex.deeplearning.DeepLearningModel
 
toString() - Method in class hex.deeplearning.Dropout
 
toString() - Method in class hex.deeplearning.Neurons.SparseVector.Iterator
 
toString() - Method in class hex.deeplearning.Neurons
Print the status of this neuron layer
toString() - Method in class hex.glm.GLM.BetaConstraint
 
toString() - Method in class hex.glm.GLMValidation
 
toString() - Method in class hex.gram.Gram.Cholesky
 
toString() - Method in class hex.gram.Gram
 
toString() - Method in class hex.optimization.L_BFGS.GradientInfo
 
toString() - Method in class hex.optimization.L_BFGS.Result
 
toString(SharedTreeModel.SharedTreeOutput) - Method in class hex.tree.CompressedTree
 
toString() - Method in class hex.tree.DHistogram
 
toString() - Method in class hex.tree.DTree.DecidedNode
 
toString() - Method in class hex.tree.DTree.LeafNode
 
toString() - Method in class hex.tree.DTree.Split
 
toString() - Method in class hex.tree.DTree.UndecidedNode
 
toString2(StringBuilder, int) - Method in class hex.tree.DTree.DecidedNode
 
toString2(StringBuilder, int) - Method in class hex.tree.DTree.LeafNode
 
toString2(StringBuilder, int) - Method in class hex.tree.DTree.Node
 
toString2(StringBuilder, int) - Method in class hex.tree.DTree.UndecidedNode
 
toStringAll() - Method in class hex.coxph.CoxPHModel
 
toStringAll() - Method in class hex.deeplearning.DeepLearningModel.DeepLearningModelInfo
 
toStringTree(int, int) - Method in class hex.tree.SharedTreeModel.SharedTreeOutput
 
total_models - Variable in class hex.GridSearchSchema
 
train(int, CoxPHV3) - Method in class hex.api.CoxPHBuilderHandler
Required so that Handler.handle() gets the correct schema types.
train(int, DeepLearningV3) - Method in class hex.api.DeepLearningBuilderHandler
Required so that Handler.handle() gets the correct schema types.
train(int, DRFV3) - Method in class hex.api.DRFBuilderHandler
Required so that Handler.handle() gets the correct schema types.
train(int, DRFGridSearchV3) - Method in class hex.api.DRFGridSearchHandler
 
train(int, ExampleV3) - Method in class hex.api.ExampleBuilderHandler
Required so that Handler.handle() gets the correct schema types.
train(int, GBMV3) - Method in class hex.api.GBMBuilderHandler
Required so that Handler.handle() gets the correct schema types.
train(int, GBMGridSearchV3) - Method in class hex.api.GBMGridSearchHandler
 
train(int, GLMV3) - Method in class hex.api.GLMBuilderHandler
Required so that Handler.handle() gets the correct schema types.
train(int, GLRMV3) - Method in class hex.api.GLRMBuilderHandler
Required so that Handler.handle() gets the correct schema types.
train(int, GrepV3) - Method in class hex.api.GrepBuilderHandler
Required so that Handler.handle() gets the correct schema types.
train(int, KMeansV3) - Method in class hex.api.KMeansBuilderHandler
Required so that Handler.handle() gets the correct schema types.
train(int, KMeansGridSearchV3) - Method in class hex.api.KMeansGridSearchHandler
 
train(int, NaiveBayesV3) - Method in class hex.api.NaiveBayesBuilderHandler
Required so that Handler.handle() gets the correct schema types.
train(int, PCAV3) - Method in class hex.api.PCABuilderHandler
Required so that Handler.handle() gets the correct schema types.
train(int, QuantileV3) - Method in class hex.api.QuantileBuilderHandler
Required so that Handler.handle() gets the correct schema types.
train(int, SVDV3) - Method in class hex.api.SVDBuilderHandler
Required so that Handler.handle() gets the correct schema types.
train(int, Word2VecV3) - Method in class hex.api.Word2VecBuilderHandler
Required so that Handler.handle() gets the correct schema types.
train_confusion_matrix - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningScoring
 
train_samples_per_iteration - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
The number of training data rows to be processed per iteration.
training_AUC - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningScoring
 
training_rows - Variable in class hex.deeplearning.DeepLearningModel
 
training_samples - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningScoring
 
training_time_ms - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningScoring
 
trainModel() - Method in class hex.coxph.CoxPH
Start the Cox PH training Job on an F/J thread.
trainModel(DeepLearningModel) - Method in class hex.deeplearning.DeepLearning.DeepLearningDriver
Train a Deep Learning neural net model
trainModel() - Method in class hex.deeplearning.DeepLearning
Start the DeepLearning training Job on an F/J thread.
trainModel() - Method in class hex.example.Example
 
trainModel() - Method in class hex.glm.GLM
 
trainModel() - Method in class hex.glrm.GLRM
 
trainModel() - Method in class hex.grep.Grep
 
trainModel() - Method in class hex.kmeans.KMeans
Start the KMeans training Job on an F/J thread.
trainModel() - Method in class hex.naivebayes.NaiveBayes
 
trainModel() - Method in class hex.pca.PCA
 
trainModel() - Method in class hex.svd.SVD
 
trainModel() - Method in class hex.tree.drf.DRF
Start the DRF training Job on an F/J thread.
trainModel() - Method in class hex.tree.gbm.GBM
Start the GBM training Job on an F/J thread.
trainModel() - Method in class hex.word2vec.Word2Vec
Start the KMeans training Job on an F/J thread.
transform(double[][], double[], double[], int, int) - Static method in class hex.glrm.GLRM
 
transform - Variable in class hex.schemas.GLRMV3.GLRMParametersV3
 
transform - Variable in class hex.schemas.PCAV3.PCAParametersV3
 
transform - Variable in class hex.schemas.SVDV3.SVDParametersV3
 
transform(String) - Method in class hex.word2vec.Word2VecModel
Takes an input string can return the word vector for that word.
TreeMeasuresCollector - Class in hex.tree.drf
Score given tree model and preserve errors per tree in form of votes (for classification) or MSE (for regression).
TreeMeasuresCollector.ShuffleTask - Class in hex.tree.drf
 
TreeMeasuresCollector.ShuffleTask() - Constructor for class hex.tree.drf.TreeMeasuresCollector.ShuffleTask
 
TreeMeasuresCollector.TreeMeasures<T extends TreeMeasuresCollector.TreeMeasures> - Class in hex.tree.drf
A simple holder for set of different tree measurements.
TreeMeasuresCollector.TreeMeasures(int) - Constructor for class hex.tree.drf.TreeMeasuresCollector.TreeMeasures
 
TreeMeasuresCollector.TreeMeasures(long[], int) - Constructor for class hex.tree.drf.TreeMeasuresCollector.TreeMeasures
 
TreeMeasuresCollector.TreeSSE - Class in hex.tree.drf
A simple holder serving SSE per tree.
TreeMeasuresCollector.TreeSSE(int) - Constructor for class hex.tree.drf.TreeMeasuresCollector.TreeSSE
 
TreeMeasuresCollector.TreeSSE(float[], long[], int) - Constructor for class hex.tree.drf.TreeMeasuresCollector.TreeSSE
 
TreeMeasuresCollector.TreeVotes - Class in hex.tree.drf
A class holding tree votes.
TreeMeasuresCollector.TreeVotes(int) - Constructor for class hex.tree.drf.TreeMeasuresCollector.TreeVotes
 
TreeMeasuresCollector.TreeVotes(long[], long[], int) - Constructor for class hex.tree.drf.TreeMeasuresCollector.TreeVotes
 
TreeStats - Class in hex.tree
 
TreeStats() - Constructor for class hex.tree.TreeStats
 
TreeStatsV3 - Class in hex.schemas
 
TreeStatsV3() - Constructor for class hex.schemas.TreeStatsV3
 
TreeVisitor<T extends java.lang.Exception> - Class in hex.tree
Abstract visitor class for serialized trees.
TreeVisitor(CompressedTree) - Constructor for class hex.tree.TreeVisitor
 
tryFork() - Method in class hex.gram.Gram.Cholesky.DelayedTask
 

U

u_key - Variable in class hex.schemas.SVDModelV3.SVDModelOutputV3
 
u_name - Variable in class hex.schemas.SVDV3.SVDParametersV3
 
undecided(int) - Method in class hex.tree.DTree
 
unit_active(int) - Method in class hex.deeplearning.Dropout
 
units - Variable in class hex.deeplearning.Neurons
 
unScaleNumericals(float[], float[]) - Method in class hex.DataInfo
Undo the standardization/normalization of numerical columns
unstable() - Method in class hex.deeplearning.DeepLearningModel.DeepLearningModelInfo
 
updateBy(DTree) - Method in class hex.tree.TreeStats
 
updateGram(double[][], double[][]) - Static method in class hex.svd.SVD
 
updateIVVSum(double[][], double[]) - Static method in class hex.svd.SVD
 
updateLearningRate() - Method in class hex.word2vec.Word2VecModel.Word2VecModelInfo
Calculates a new global learning rate for the next round of map/reduce calls.
use_all_factor_levels - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
 
use_all_factor_levels - Variable in class hex.schemas.PCAV3.PCAParametersV3
 
use_all_factor_levels - Variable in class hex.schemas.SVDV3.SVDParametersV3
 
user_points - Variable in class hex.schemas.GLRMV3.GLRMParametersV3
 
user_points - Variable in class hex.schemas.KMeansV3.KMeansParametersV3
 

V

v - Variable in class hex.schemas.SVDModelV3.SVDModelOutputV3
 
valid_confusion_matrix - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningScoring
 
validate(GLM) - Method in class hex.glm.GLMModel.GLMParameters
 
validate_parameters(int, CoxPHV3) - Method in class hex.api.CoxPHBuilderHandler
Required so that Handler.handle() gets the correct schema types.
validate_parameters(int, DeepLearningV3) - Method in class hex.api.DeepLearningBuilderHandler
Required so that Handler.handle() gets the correct schema types.
validate_parameters(int, DRFV3) - Method in class hex.api.DRFBuilderHandler
Required so that Handler.handle() gets the correct schema types.
validate_parameters(int, ExampleV3) - Method in class hex.api.ExampleBuilderHandler
Required so that Handler.handle() gets the correct schema types.
validate_parameters(int, GBMV3) - Method in class hex.api.GBMBuilderHandler
Required so that Handler.handle() gets the correct schema types.
validate_parameters(int, GLMV3) - Method in class hex.api.GLMBuilderHandler
Required so that Handler.handle() gets the correct schema types.
validate_parameters(int, GLRMV3) - Method in class hex.api.GLRMBuilderHandler
Required so that Handler.handle() gets the correct schema types.
validate_parameters(int, GrepV3) - Method in class hex.api.GrepBuilderHandler
Required so that Handler.handle() gets the correct schema types.
validate_parameters(int, KMeansV3) - Method in class hex.api.KMeansBuilderHandler
Required so that Handler.handle() gets the correct schema types.
validate_parameters(int, NaiveBayesV3) - Method in class hex.api.NaiveBayesBuilderHandler
Required so that Handler.handle() gets the correct schema types.
validate_parameters(int, PCAV3) - Method in class hex.api.PCABuilderHandler
Required so that Handler.handle() gets the correct schema types.
validate_parameters(int, QuantileV3) - Method in class hex.api.QuantileBuilderHandler
Required so that Handler.handle() gets the correct schema types.
validate_parameters(int, SVDV3) - Method in class hex.api.SVDBuilderHandler
Required so that Handler.handle() gets the correct schema types.
validate_parameters(int, Word2VecV3) - Method in class hex.api.Word2VecBuilderHandler
Required so that Handler.handle() gets the correct schema types.
validation_AUC - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningScoring
 
validation_rows - Variable in class hex.deeplearning.DeepLearningModel
 
validDinfo(Frame) - Method in class hex.DataInfo
 
valueOf(String) - Static method in enum hex.coxph.CoxPHModel.CoxPHParameters.CoxPHTies
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum hex.DataInfo.TransformType
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum hex.deeplearning.DeepLearningModel.DeepLearningParameters.Activation
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum hex.deeplearning.DeepLearningModel.DeepLearningParameters.ClassSamplingMethod
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum hex.deeplearning.DeepLearningModel.DeepLearningParameters.InitialWeightDistribution
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum hex.deeplearning.DeepLearningModel.DeepLearningParameters.Loss
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum hex.deeplearning.DeepLearningModel.DeepLearningParameters.MissingValuesHandling
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum hex.glm.GLMModel.GLMParameters.Family
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum hex.glm.GLMModel.GLMParameters.Link
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum hex.glm.GLMModel.GLMParameters.Solver
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum hex.glrm.GLRM.Initialization
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum hex.glrm.GLRMModel.GLRMParameters.Loss
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum hex.glrm.GLRMModel.GLRMParameters.MultiLoss
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum hex.glrm.GLRMModel.GLRMParameters.Regularizer
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum hex.kmeans.KMeans.Initialization
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum hex.pca.PCA.Initialization
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum hex.tree.gbm.GBMModel.GBMParameters.Family
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum hex.word2vec.Word2Vec.NormModel
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum hex.word2vec.Word2Vec.WordModel
Returns the enum constant of this type with the specified name.
values() - Static method in enum hex.coxph.CoxPHModel.CoxPHParameters.CoxPHTies
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum hex.DataInfo.TransformType
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum hex.deeplearning.DeepLearningModel.DeepLearningParameters.Activation
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum hex.deeplearning.DeepLearningModel.DeepLearningParameters.ClassSamplingMethod
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum hex.deeplearning.DeepLearningModel.DeepLearningParameters.InitialWeightDistribution
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum hex.deeplearning.DeepLearningModel.DeepLearningParameters.Loss
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum hex.deeplearning.DeepLearningModel.DeepLearningParameters.MissingValuesHandling
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum hex.glm.GLMModel.GLMParameters.Family
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum hex.glm.GLMModel.GLMParameters.Link
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum hex.glm.GLMModel.GLMParameters.Solver
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum hex.glrm.GLRM.Initialization
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum hex.glrm.GLRMModel.GLRMParameters.Loss
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum hex.glrm.GLRMModel.GLRMParameters.MultiLoss
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum hex.glrm.GLRMModel.GLRMParameters.Regularizer
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum hex.kmeans.KMeans.Initialization
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum hex.pca.PCA.Initialization
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum hex.tree.gbm.GBMModel.GBMParameters.Family
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum hex.word2vec.Word2Vec.NormModel
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum hex.word2vec.Word2Vec.WordModel
Returns an array containing the constants of this enum type, in the order they are declared.
var(int) - Method in class hex.tree.DBinomHistogram
 
var(int) - Method in class hex.tree.DHistogram
 
var(int) - Method in class hex.tree.DRealHistogram
 
variable_importances - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
Whether to compute variable importances for input features.
variance(double) - Method in class hex.glm.GLMModel.GLMParameters
 
varImp() - Method in class hex.deeplearning.DeepLearningModel
 
varImp() - Method in class hex.tree.SharedTreeModel
 
vec_nids(Frame, int) - Method in class hex.tree.SharedTree
 
vec_resp(Frame) - Method in class hex.tree.SharedTree
 
vec_tree(Frame, int) - Method in class hex.tree.SharedTree
 
vecSize - Variable in class hex.schemas.Word2VecV3.Word2VecParametersV3
 
visit() - Method in class hex.tree.TreeVisitor
 
votes() - Method in class hex.tree.drf.TreeMeasuresCollector.TreeVotes
Returns number of positive votes per tree.
vresponse() - Method in class hex.tree.SharedTree
 

W

water.api - package water.api
 
weight - Variable in class hex.DataInfo.Row
 
weightChunkId() - Method in class hex.DataInfo
 
weights_column - Variable in class hex.coxph.CoxPHModel.CoxPHParameters
 
weights_column - Variable in class hex.schemas.GLMV3.GLMParametersV3
 
windowSize - Variable in class hex.schemas.Word2VecV3.Word2VecParametersV3
 
Word2Vec - Class in hex.word2vec
 
Word2Vec(Word2VecModel.Word2VecParameters) - Constructor for class hex.word2vec.Word2Vec
 
Word2Vec.NormModel - Enum in hex.word2vec
 
Word2Vec.WordModel - Enum in hex.word2vec
 
Word2VecBuilderHandler - Class in hex.api
 
Word2VecBuilderHandler() - Constructor for class hex.api.Word2VecBuilderHandler
 
Word2VecModel - Class in hex.word2vec
 
Word2VecModel(Key, Word2VecModel.Word2VecParameters, Word2VecModel.Word2VecOutput) - Constructor for class hex.word2vec.Word2VecModel
 
Word2VecModel.Word2VecModelInfo - Class in hex.word2vec
 
Word2VecModel.Word2VecModelInfo() - Constructor for class hex.word2vec.Word2VecModel.Word2VecModelInfo
 
Word2VecModel.Word2VecModelInfo(Word2VecModel.Word2VecParameters) - Constructor for class hex.word2vec.Word2VecModel.Word2VecModelInfo
 
Word2VecModel.Word2VecOutput - Class in hex.word2vec
 
Word2VecModel.Word2VecOutput(Word2Vec) - Constructor for class hex.word2vec.Word2VecModel.Word2VecOutput
 
Word2VecModel.Word2VecParameters - Class in hex.word2vec
 
Word2VecModel.Word2VecParameters() - Constructor for class hex.word2vec.Word2VecModel.Word2VecParameters
 
Word2VecModelV3 - Class in hex.schemas
 
Word2VecModelV3() - Constructor for class hex.schemas.Word2VecModelV3
 
Word2VecModelV3.Word2VecModelOutputV3 - Class in hex.schemas
 
Word2VecModelV3.Word2VecModelOutputV3() - Constructor for class hex.schemas.Word2VecModelV3.Word2VecModelOutputV3
 
Word2VecV3 - Class in hex.schemas
 
Word2VecV3() - Constructor for class hex.schemas.Word2VecV3
 
Word2VecV3.Word2VecParametersV3 - Class in hex.schemas
 
Word2VecV3.Word2VecParametersV3() - Constructor for class hex.schemas.Word2VecV3.Word2VecParametersV3
 
WordCountTask - Class in hex.word2vec
Reduce all string columns frame to a set of unique words and their frequency counts
WordCountTask() - Constructor for class hex.word2vec.WordCountTask
 
WordCountTask(int) - Constructor for class hex.word2vec.WordCountTask
 
WordCountTask.ValueStringCount - Class in hex.word2vec
Small extension to the ValueString class to add an atomic counter for each word.
WordCountTask.ValueStringCount() - Constructor for class hex.word2vec.WordCountTask.ValueStringCount
 
wordModel - Variable in class hex.schemas.Word2VecV3.Word2VecParametersV3
 
WordVectorTrainer - Class in hex.word2vec
 
WordVectorTrainer(Word2VecModel.Word2VecModelInfo) - Constructor for class hex.word2vec.WordVectorTrainer
 
write_impl(AutoBuffer) - Method in class hex.word2vec.WordCountTask
Automagically called as a node sends its results to be reduced by another node.

Y

yt_block(double[][], int, DataInfo) - Static method in class hex.glrm.GLRM
 
yt_block(double[][], int, DataInfo, boolean) - Static method in class hex.glrm.GLRM
 

_

_a - Variable in class hex.deeplearning.Neurons
Layer state (one per neuron): activity, error
_activation - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
The activation function (non-linearity) to be used the neurons in the hidden layers.
_activeCols - Variable in class hex.DataInfo
 
_adaptedFrame - Variable in class hex.DataInfo
 
_adaptive_rate - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
The implemented adaptive learning rate algorithm (ADADELTA) automatically combines the benefits of learning rate annealing and momentum training to avoid slow convergence.
_alpha - Variable in class hex.glm.GLMModel.GLMParameters
 
_apriori - Variable in class hex.naivebayes.NaiveBayesModel.NaiveBayesOutput
 
_apriori_raw - Variable in class hex.naivebayes.NaiveBayesModel.NaiveBayesOutput
 
_archetypes - Variable in class hex.glrm.GLRMModel.GLRMOutput
 
_autoencoder - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
 
_average_activation - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
 
_avg_a - Variable in class hex.deeplearning.Neurons
 
_avg_centroids_chg - Variable in class hex.kmeans.KMeansModel.KMeansOutput
 
_avg_change_obj - Variable in class hex.glrm.GLRMModel.GLRMOutput
 
_b - Variable in class hex.deeplearning.Neurons
 
_best_lambda_idx - Variable in class hex.glm.GLMModel.GLMOutput
 
_beta_constraints - Variable in class hex.glm.GLMModel.GLMParameters
 
_beta_epsilon - Variable in class hex.glm.GLMModel.GLMParameters
 
_betweenss - Variable in class hex.kmeans.KMeansModel.KMeansOutput
 
_bin - Variable in class hex.tree.DTree.Split
 
_binomial - Variable in class hex.glm.GLMModel.GLMOutput
 
_binomial_double_trees - Variable in class hex.tree.drf.DRFModel.DRFParameters
 
_bins - Variable in class hex.DataInfo
 
_bins - Variable in class hex.tree.DHistogram
 
_build_tree_one_node - Variable in class hex.tree.drf.DRFModel.DRFParameters
 
_byte_size - Variable in class hex.tree.TreeStats
 
_categorical_column_count - Variable in class hex.kmeans.KMeansModel.KMeansOutput
 
_catMissing - Variable in class hex.DataInfo
 
_catOffsets - Variable in class hex.DataInfo
 
_catOffsets - Variable in class hex.pca.PCAModel.PCAOutput
 
_catOffsets - Variable in class hex.svd.SVDModel.SVDOutput
 
_cats - Variable in class hex.DataInfo
 
_checkpoint - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
A model key associated with a previously trained Deep Learning model.
_checkpoint - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters
 
_classification_stop - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
The stopping criteria in terms of classification error (1-accuracy) on the training data scoring dataset.
_col - Variable in class hex.tree.DTree.Split
 
_col_major - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
 
_compute_metrics - Variable in class hex.naivebayes.NaiveBayesModel.NaiveBayesParameters
 
_ct - Variable in class hex.tree.TreeVisitor
 
_d - Variable in class hex.svd.SVDModel.SVDOutput
 
_depth - Variable in class hex.tree.DTree
 
_depth - Variable in class hex.tree.TreeVisitor
 
_diag - Variable in class hex.gram.Gram.Cholesky
 
_diagAdded - Variable in class hex.gram.Gram
 
_diagN - Variable in class hex.gram.Gram
 
_diagnostics - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
Gather diagnostics for hidden layers, such as mean and RMS values of learning rate, momentum, weights and biases.
_dinfo - Variable in class hex.FrameTask
 
_distribution - Variable in class hex.tree.gbm.GBMModel.GBMParameters
 
_dropout - Variable in class hex.deeplearning.Neurons
For Dropout training
_e - Variable in class hex.deeplearning.Neurons
 
_eigenvectors - Variable in class hex.glrm.GLRMModel.GLRMOutput
 
_eigenvectors - Variable in class hex.pca.PCAModel.PCAOutput
 
_eigenvectors_raw - Variable in class hex.glrm.GLRMModel.GLRMOutput
 
_eigenvectors_raw - Variable in class hex.pca.PCAModel.PCAOutput
 
_epochs - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
The number of passes over the training dataset to be carried out.
_epochs - Variable in class hex.word2vec.Word2VecModel.Word2VecOutput
 
_epochs - Variable in class hex.word2vec.Word2VecModel.Word2VecParameters
 
_eps_prob - Variable in class hex.naivebayes.NaiveBayesModel.NaiveBayesParameters
 
_eps_sdev - Variable in class hex.naivebayes.NaiveBayesModel.NaiveBayesParameters
 
_epsilon - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
The second of two hyper parameters for adaptive learning rate (ADADELTA).
_exactLambdas - Variable in class hex.glm.GLMModel.GLMParameters
 
_export_weights_and_biases - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
 
_family - Variable in class hex.glm.GLMModel.GLMParameters
 
_fast_mode - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
Enable fast mode (minor approximation in back-propagation), should not affect results significantly.
_force_load_balance - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
Increase training speed on small datasets by splitting it into many chunks to allow utilization of all cores.
_gamma_x - Variable in class hex.glrm.GLRMModel.GLRMParameters
 
_gamma_y - Variable in class hex.glrm.GLRMModel.GLRMParameters
 
_gradient - Variable in class hex.optimization.L_BFGS.GradientInfo
 
_gradient_epsilon - Variable in class hex.glm.GLMModel.GLMParameters
 
_gram - Variable in class hex.glm.GLMTask.GLMIterationTask
 
_gram - Variable in class hex.gram.Gram.GramTask
 
_hidden - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
The number and size of each hidden layer in the model.
_hidden_dropout_ratios - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
A fraction of the inputs for each hidden layer to be omitted from training in order to improve generalization.
_history_withinss - Variable in class hex.kmeans.KMeansModel.KMeansOutput
 
_hs - Variable in class hex.tree.DTree.UndecidedNode
 
_index - Variable in class hex.deeplearning.Neurons
 
_init - Variable in class hex.glrm.GLRMModel.GLRMParameters
 
_init - Variable in class hex.kmeans.KMeansModel.KMeansParameters
 
_init_f - Variable in class hex.tree.SharedTreeModel.SharedTreeOutput
InitF value (for zero trees) f0 = mean(yi) for gaussian f0 = log(yi/1-yi) for bernoulli For GBM bernoulli, the initial prediction for 0 trees is p = 1/(1+exp(-f0)) From this, the mse for 0 trees can be computed as follows: mean((yi-p)^2) This is what is stored in _scored_train[0]
_init_step_size - Variable in class hex.glrm.GLRMModel.GLRMParameters
 
_initial_weight_distribution - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
The distribution from which initial weights are to be drawn.
_initial_weight_scale - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
The scale of the distribution function for Uniform or Normal distributions.
_initialPrediction - Variable in class hex.tree.SharedTree
 
_initLearningRate - Variable in class hex.word2vec.Word2VecModel.Word2VecOutput
 
_initLearningRate - Variable in class hex.word2vec.Word2VecModel.Word2VecParameters
 
_input - Variable in class hex.deeplearning.Neurons
 
_input_dropout_ratio - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
A fraction of the features for each training row to be omitted from training in order to improve generalization (dimension sampling).
_intercept - Variable in class hex.DataInfo
 
_isInt - Variable in class hex.tree.DHistogram
 
_iter - Variable in class hex.glm.GLM.LBFGS_ProximalSolver
 
_iterations - Variable in class hex.example.ExampleModel.ExampleOutput
 
_iterations - Variable in class hex.glrm.GLRMModel.GLRMOutput
 
_iterations - Variable in class hex.kmeans.KMeansModel.KMeansOutput
 
_jobKey - Variable in class hex.FrameTask
 
_k - Variable in class hex.glrm.GLRMModel.GLRMParameters
 
_k - Variable in class hex.pca.PCAModel.PCAParameters
 
_keep_cross_validation_splits - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
 
_keep_loading - Variable in class hex.pca.PCAModel.PCAParameters
 
_keep_u - Variable in class hex.svd.SVDModel.SVDParameters
 
_l1 - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
A regularization method that constrains the absolute value of the weights and has the net effect of dropping some weights (setting them to zero) from a model to reduce complexity and avoid overfitting.
_l2 - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
A regularization method that constrdains the sum of the squared weights.
_lambda - Variable in class hex.glm.GLMModel.GLMParameters
 
_lambda_max - Variable in class hex.glm.GLMModel
 
_lambda_min_ratio - Variable in class hex.glm.GLMModel.GLMParameters
 
_lambda_search - Variable in class hex.glm.GLMModel.GLMParameters
 
_laplace - Variable in class hex.naivebayes.NaiveBayesModel.NaiveBayesParameters
 
_learn_rate - Variable in class hex.tree.gbm.GBMModel.GBMParameters
 
_leaves - Variable in class hex.tree.DTree
 
_len - Variable in class hex.tree.DTree
 
_levels - Variable in class hex.naivebayes.NaiveBayesModel.NaiveBayesOutput
 
_likelihood - Variable in class hex.glm.GLMTask.GLMIterationTask
 
_lineSearch - Variable in class hex.glm.GLM.GLMTaskInfo
 
_link - Variable in class hex.glm.GLMModel.GLMParameters
 
_loading_key - Variable in class hex.glrm.GLRMModel.GLRMOutput
 
_loading_key - Variable in class hex.glrm.GLRMModel.GLRMParameters
 
_loading_key - Variable in class hex.pca.PCAModel.PCAOutput
 
_loading_name - Variable in class hex.pca.PCAModel.PCAParameters
 
_loss - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
The loss (error) function to be minimized by the model.
_loss - Variable in class hex.glrm.GLRMModel.GLRMParameters
 
_lsCnt - Variable in class hex.glm.GLM.GLMTaskInfo
 
_matches - Variable in class hex.grep.GrepModel.GrepOutput
 
_max_active_predictors - Variable in class hex.glm.GLMModel.GLMParameters
 
_max_categorical_features - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
Max.
_max_depth - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters
 
_max_depth - Variable in class hex.tree.TreeStats
 
_max_iterations - Variable in class hex.example.ExampleModel.ExampleParameters
 
_max_iterations - Variable in class hex.glm.GLMModel.GLMParameters
 
_max_iterations - Variable in class hex.glrm.GLRMModel.GLRMParameters
 
_max_iterations - Variable in class hex.kmeans.KMeansModel.KMeansParameters
 
_max_iterations - Variable in class hex.pca.PCAModel.PCAParameters
 
_max_iterations - Variable in class hex.svd.SVDModel.SVDParameters
 
_max_leaves - Variable in class hex.tree.TreeStats
 
_max_w2 - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
A maximum on the sum of the squared incoming weights into any one neuron.
_maxEx - Variable in class hex.tree.DHistogram
 
_maxIn - Variable in class hex.tree.DHistogram
 
_maxs - Variable in class hex.example.ExampleModel.ExampleOutput
 
_mean_depth - Variable in class hex.tree.TreeStats
 
_mean_leaves - Variable in class hex.tree.TreeStats
 
_min - Variable in class hex.tree.DHistogram
 
_min2 - Variable in class hex.tree.DHistogram
 
_min_depth - Variable in class hex.tree.TreeStats
 
_min_leaves - Variable in class hex.tree.TreeStats
 
_min_prob - Variable in class hex.naivebayes.NaiveBayesModel.NaiveBayesParameters
 
_min_rows - Variable in class hex.tree.DTree
 
_min_rows - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters
 
_min_sdev - Variable in class hex.naivebayes.NaiveBayesModel.NaiveBayesParameters
 
_min_step_size - Variable in class hex.glrm.GLRMModel.GLRMParameters
 
_minWordFreq - Variable in class hex.word2vec.Word2VecModel.Word2VecOutput
 
_minWordFreq - Variable in class hex.word2vec.Word2VecModel.Word2VecParameters
 
_missing_values_handling - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
 
_model - Variable in class hex.tree.SharedTree
 
_momentum_ramp - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
The momentum_ramp parameter controls the amount of learning for which momentum increases (assuming momentum_stable is larger than momentum_start).
_momentum_stable - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
The momentum_stable parameter controls the final momentum value reached after momentum_ramp training samples.
_momentum_start - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
The momentum_start parameter controls the amount of momentum at the beginning of training.
_mtry - Variable in class hex.tree.drf.DRF
 
_multi_loss - Variable in class hex.glrm.GLRMModel.GLRMParameters
 
_n_folds - Variable in class hex.glm.GLMModel.GLMParameters
 
_name - Variable in class hex.tree.DHistogram
 
_names_expanded - Variable in class hex.svd.SVDModel.SVDOutput
 
_nbin - Variable in class hex.tree.DHistogram
 
_nbins - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters
 
_nbins_cats - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters
 
_nbins_top_level - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters
 
_ncats - Variable in class hex.naivebayes.NaiveBayesModel.NaiveBayesOutput
 
_ncats - Variable in class hex.pca.PCAModel.PCAOutput
 
_ncats - Variable in class hex.svd.SVDModel.SVDOutput
 
_nclass - Variable in class hex.tree.DTreeScorer
 
_ncols - Variable in class hex.tree.DTreeScorer
 
_ncols - Variable in class hex.tree.SharedTree
 
_negSampleCnt - Variable in class hex.word2vec.Word2VecModel.Word2VecOutput
 
_negSampleCnt - Variable in class hex.word2vec.Word2VecModel.Word2VecParameters
 
_nesterov_accelerated_gradient - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
The Nesterov accelerated gradient descent method is a modification to traditional gradient descent for convex functions.
_nid - Variable in class hex.tree.DTree.Node
 
_nids - Variable in class hex.tree.DTree.DecidedNode
 
_nlambdas - Variable in class hex.glm.GLMModel.GLMParameters
 
_nnums - Variable in class hex.pca.PCAModel.PCAOutput
 
_nnums - Variable in class hex.svd.SVDModel.SVDOutput
 
_nobs - Variable in class hex.glm.GLMModel
 
_nobs - Variable in class hex.gram.Gram.GramTask
 
_nobs - Variable in class hex.svd.SVDModel.SVDOutput
 
_nodes - Variable in class hex.tree.TreeVisitor
 
_non_negative - Variable in class hex.glm.GLMModel.GLMParameters
 
_normModel - Variable in class hex.word2vec.Word2VecModel.Word2VecOutput
 
_normModel - Variable in class hex.word2vec.Word2VecModel.Word2VecParameters
 
_normMul - Variable in class hex.DataInfo
 
_normMul - Variable in class hex.glrm.GLRMModel.GLRMOutput
 
_normMul - Variable in class hex.pca.PCAModel.PCAOutput
 
_normMul - Variable in class hex.svd.SVDModel.SVDOutput
 
_normRespMul - Variable in class hex.DataInfo
 
_normRespSub - Variable in class hex.DataInfo
 
_normSub - Variable in class hex.DataInfo
 
_normSub - Variable in class hex.glrm.GLRMModel.GLRMOutput
 
_normSub - Variable in class hex.pca.PCAModel.PCAOutput
 
_normSub - Variable in class hex.svd.SVDModel.SVDOutput
 
_nrows - Variable in class hex.tree.drf.TreeMeasuresCollector.TreeMeasures
Number of processed row per tree.
_ntrees - Variable in class hex.tree.drf.TreeMeasuresCollector.TreeMeasures
Actual number of trees which votes are stored in this object
_ntrees - Variable in class hex.tree.SharedTree
 
_ntrees - Variable in class hex.tree.SharedTreeModel.SharedTreeOutput
Number of trees actually in the model (as opposed to requested)
_ntrees - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters
 
_num_trees - Variable in class hex.tree.TreeStats
 
_nums - Variable in class hex.DataInfo
 
_nv - Variable in class hex.svd.SVDModel.SVDParameters
 
_objective - Variable in class hex.glrm.GLRMModel.GLRMOutput
 
_objective_epsilon - Variable in class hex.glm.GLMModel.GLMParameters
 
_objVal - Variable in class hex.optimization.L_BFGS.GradientInfo
 
_offset - Variable in class hex.DataInfo
 
_offsets - Variable in class hex.grep.GrepModel.GrepOutput
 
_only_v - Variable in class hex.svd.SVDModel.SVDParameters
 
_overwrite_with_best_model - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
If enabled, store the best model under the destination key of this model at the end of training.
_pc_importance - Variable in class hex.glrm.GLRMModel.GLRMOutput
 
_pc_importance - Variable in class hex.pca.PCAModel.PCAOutput
 
_pcond - Variable in class hex.naivebayes.NaiveBayesModel.NaiveBayesOutput
 
_pcond_raw - Variable in class hex.naivebayes.NaiveBayesModel.NaiveBayesOutput
 
_permutation - Variable in class hex.DataInfo
 
_permutation - Variable in class hex.pca.PCAModel.PCAOutput
 
_permutation - Variable in class hex.svd.SVDModel.SVDOutput
 
_pid - Variable in class hex.tree.DTree.Node
 
_pred - Variable in class hex.tree.DTree.LeafNode
 
_predictor_transform - Variable in class hex.DataInfo
 
_previous - Variable in class hex.deeplearning.Neurons
References for feed-forward connectivity
_prior - Variable in class hex.glm.GLMModel.GLMParameters
 
_quiet_mode - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
Enable quiet mode for less output to standard output.
_r2_stopping - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters
 
_rate - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
When adaptive learning rate is disabled, the magnitude of the weight updates are determined by the user specified learning rate (potentially annealed), and are a function of the difference between the predicted value and the target value.
_rate_annealing - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
Learning rate annealing reduces the learning rate to "freeze" into local minima in the optimization landscape.
_rate_decay - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
The learning rate decay parameter controls the change of learning rate across layers.
_recover_pca - Variable in class hex.glrm.GLRMModel.GLRMParameters
 
_regex - Variable in class hex.grep.GrepModel.GrepParameters
 
_regression_stop - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
The stopping criteria in terms of regression error (MSE) on the training data scoring dataset.
_regularization_x - Variable in class hex.glrm.GLRMModel.GLRMParameters
 
_regularization_y - Variable in class hex.glrm.GLRMModel.GLRMParameters
 
_replicate_training_data - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
Replicate the entire training dataset onto every node for faster training on small datasets.
_reproducible - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
Force reproducibility on small data (will be slow - only uses 1 thread)
_rescnt - Variable in class hex.naivebayes.NaiveBayesModel.NaiveBayesOutput
 
_response_transform - Variable in class hex.DataInfo
 
_responses - Variable in class hex.DataInfo
 
_rho - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
The first of two hyper parameters for adaptive learning rate (ADADELTA).
_score_duty_cycle - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
Maximum fraction of wall clock time spent on model scoring on training and validation samples, and on diagnostics such as computation of feature importances (i.e., not on training).
_score_interval - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
The minimum time (in seconds) to elapse between model scoring.
_score_training_samples - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
The number of training dataset points to be used for scoring.
_score_validation_samples - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
The number of validation dataset points to be used for scoring.
_score_validation_sampling - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
Method used to sample the validation dataset for scoring, see Score Validation Samples above.
_scoreCols - Variable in class hex.tree.DTree.UndecidedNode
 
_scored_train - Variable in class hex.tree.SharedTreeModel.SharedTreeOutput
 
_scored_valid - Variable in class hex.tree.SharedTreeModel.SharedTreeOutput
 
_seed - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
The random seed controls sampling and initialization.
_seed - Variable in class hex.glrm.GLRMModel.GLRMParameters
 
_seed - Variable in class hex.kmeans.KMeansModel.KMeansParameters
 
_seed - Variable in class hex.pca.PCAModel.PCAParameters
 
_seed - Variable in class hex.svd.SVDModel.SVDParameters
 
_seed - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters
 
_sentSampleRate - Variable in class hex.word2vec.Word2VecModel.Word2VecOutput
 
_sentSampleRate - Variable in class hex.word2vec.Word2VecModel.Word2VecParameters
 
_shuffle - Variable in class hex.FrameTask
 
_shuffle_training_data - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
Enable shuffling of training data (on each node).
_single_node_mode - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
Run on a single node for fine-tuning of model parameters.
_size - Variable in class hex.kmeans.KMeansModel.KMeansOutput
 
_skipMissing - Variable in class hex.DataInfo
 
_solver - Variable in class hex.glm.GLMModel.GLMParameters
 
_sparse - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
 
_sparsity_beta - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
 
_splat - Variable in class hex.tree.DTree.DecidedNode
 
_split - Variable in class hex.tree.DTree.DecidedNode
 
_standardize - Variable in class hex.glm.GLMModel.GLMParameters
 
_standardize - Variable in class hex.kmeans.KMeansModel.KMeansParameters
 
_std_deviation - Variable in class hex.glrm.GLRMModel.GLRMOutput
 
_std_deviation - Variable in class hex.pca.PCAModel.PCAOutput
 
_step - Variable in class hex.tree.DHistogram
 
_step_size - Variable in class hex.glrm.GLRMModel.GLRMOutput
 
_sums - Variable in class hex.tree.DBinomHistogram
 
_target_ratio_comm_to_comp - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
 
_timeLastScoreEnter - Variable in class hex.deeplearning.DeepLearningModel
 
_tot_withinss - Variable in class hex.kmeans.KMeansModel.KMeansOutput
 
_totss - Variable in class hex.kmeans.KMeansModel.KMeansOutput
 
_train_samples_per_iteration - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
The number of training data rows to be processed per iteration.
_training_time_ms - Variable in class hex.kmeans.KMeansModel.KMeansOutput
 
_training_time_ms - Variable in class hex.tree.SharedTreeModel.SharedTreeOutput
Training time
_transform - Variable in class hex.glrm.GLRMModel.GLRMParameters
 
_transform - Variable in class hex.pca.PCAModel.PCAParameters
 
_transform - Variable in class hex.svd.SVDModel.SVDParameters
 
_tree - Variable in class hex.tree.DTree.Node
 
_treeKeys - Variable in class hex.tree.DTreeScorer
 
_treeKeys - Variable in class hex.tree.SharedTreeModel.SharedTreeOutput
Trees get big, so store each one seperately in the DKV.
_trees - Variable in class hex.tree.DTreeScorer
 
_treeStats - Variable in class hex.tree.SharedTreeModel.SharedTreeOutput
More indepth tree stats
_tweedie_link_power - Variable in class hex.glm.GLMModel.GLMParameters
 
_tweedie_variance_power - Variable in class hex.glm.GLMModel.GLMParameters
 
_u_key - Variable in class hex.svd.SVDModel.SVDOutput
 
_u_name - Variable in class hex.svd.SVDModel.SVDParameters
 
_use_all_factor_levels - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
 
_use_all_factor_levels - Variable in class hex.glm.GLMModel.GLMParameters
 
_use_all_factor_levels - Variable in class hex.pca.PCAModel.PCAParameters
 
_use_all_factor_levels - Variable in class hex.svd.SVDModel.SVDParameters
 
_useAllFactorLevels - Variable in class hex.DataInfo
 
_useFraction - Variable in class hex.FrameTask
 
_user_points - Variable in class hex.glrm.GLRMModel.GLRMParameters
 
_user_points - Variable in class hex.kmeans.KMeansModel.KMeansParameters
 
_v - Variable in class hex.svd.SVDModel.SVDOutput
 
_valid - Variable in class hex.DataInfo
 
_variable_importances - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningModelOutput
 
_variable_importances - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
Whether to compute variable importances for input features.
_variable_importances - Variable in class hex.tree.SharedTreeModel.SharedTreeOutput
Variable importances computed during training
_varimp - Variable in class hex.tree.SharedTreeModel.SharedTreeOutput
 
_vecSize - Variable in class hex.word2vec.Word2VecModel.Word2VecOutput
 
_vecSize - Variable in class hex.word2vec.Word2VecModel.Word2VecParameters
 
_vocabKey - Variable in class hex.word2vec.Word2VecModel.Word2VecParameters
 
_w - Variable in class hex.deeplearning.Neurons
 
_weights - Variable in class hex.DataInfo
 
_windowSize - Variable in class hex.word2vec.Word2VecModel.Word2VecOutput
 
_windowSize - Variable in class hex.word2vec.Word2VecModel.Word2VecParameters
 
_withinss - Variable in class hex.kmeans.KMeansModel.KMeansOutput
 
_wordModel - Variable in class hex.word2vec.Word2VecModel.Word2VecOutput
 
_wordModel - Variable in class hex.word2vec.Word2VecModel.Word2VecParameters
 
_xx - Variable in class hex.gram.Gram
 
_xx - Variable in class hex.gram.Gram.Cholesky
 
_ymu - Variable in class hex.glm.GLMModel
 
_ySigma - Variable in class hex.glm.GLMModel
 
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