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

A

acceptsFrame(Frame) - Method in class hex.schemas.DeepLearningV2

acceptsFrame(Frame) - Method in class hex.schemas.ExampleV2

acceptsFrame(Frame) - Method in class hex.schemas.GBMV2

acceptsFrame(Frame) - Method in class hex.schemas.GLMV2

acceptsFrame(Frame) - Method in class hex.schemas.GrepV2

acceptsFrame(Frame) - Method in class hex.schemas.KMeansV2

acceptsFrame(Frame) - Method in class hex.schemas.PCAV2

acceptsFrame(Frame) - Method in class hex.schemas.QuantileV2

acceptsFrame(Frame) - Method in class hex.schemas.SplitFrameV2

acceptsFrame(Frame) - Method in class hex.schemas.Word2VecV2

activation - Variable in class hex.schemas.DeepLearningV2.DeepLearningParametersV2

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.DeepLearningV2.DeepLearningParametersV2

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) - Method in class hex.glm.GLMValidation

add(GLMValidation) - 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

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

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

aic() - Method in class hex.glm.GLMValidation

alpha - Variable in class hex.schemas.GLMV2.GLMParametersV2

ary2str(StringBuilder, int, long[]) - Static method in class hex.tree.DTree.Split

ary2str(StringBuilder, int, float[]) - Static method in class hex.tree.DTree.Split

ary2str(StringBuilder, int, double[]) - Static method in class hex.tree.DTree.Split

auc() - Method in class hex.glm.GLMValidation

auc - Variable in class hex.schemas.SharedTreeV2.SharedTreeParametersV2

AUC for binomial models, or null otherwise

autoencoder - Variable in class hex.schemas.DeepLearningV2.DeepLearningParametersV2

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.DeepLearningV2.DeepLearningParametersV2

avgbetweenss - Variable in class hex.schemas.KMeansModelV2.KMeansModelOutputV2

avgss - Variable in class hex.schemas.KMeansModelV2.KMeansModelOutputV2

avgwithinss - Variable in class hex.schemas.KMeansModelV2.KMeansModelOutputV2

B

begin() - Method in class hex.deeplearning.Neurons.SparseVector

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

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

bin(Chunk[], int) - Method in class hex.tree.DTree.DecidedNode

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

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

buildLayer(Frame, 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

calcSummaryTable() - Method in class hex.deeplearning.DeepLearningModel.DeepLearningModelInfo

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.grep.Grep

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

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

can_build() - Method in class hex.quantile.Quantile

can_build() - Method in class hex.splitframe.SplitFrame

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

catOffsets - Variable in class hex.schemas.PCAModelV2.PCAModelOutputV2

centers - Variable in class hex.schemas.KMeansModelV2.KMeansModelOutputV2

centersraw - Variable in class hex.schemas.KMeansModelV2.KMeansModelOutputV2

checkKKTAndComplete(double[], boolean) - Method in class hex.glm.GLM.GLMLambdaTask

Computes the full gradient (gradient for all predictors) and checks line search condition (gradient has no NaNs/Infs) and the KKT conditions for the underlying optimization problem.

checkpoint - Variable in class hex.schemas.DeepLearningV2.DeepLearningParametersV2

A model key associated with a previously trained Deep Learning model.

checksum_impl() - Method in class hex.FrameTask.DataInfo

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

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

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.glm.GLMTask.GLMIterationTask

chunkDone(long) - Method in class hex.glm.GLMTask.GLMLineSearchTask

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.glm.GLMTask.GLMIterationTask

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

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

classification - Variable in class hex.deeplearning.DeepLearningModel.Errors

classification_stop - Variable in class hex.schemas.DeepLearningV2.DeepLearningParametersV2

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.glm.GLMTask.GLMLineSearchTask

closeLocal() - Method in class hex.word2vec.WordVectorTrainer

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

for grid search error reporting

cm - Variable in class hex.schemas.SharedTreeV2.SharedTreeParametersV2

Confusion Matrix for classification models, or null otherwise

cnt - Variable in class hex.schemas.SynonymV1

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

get beta coefficients in a map indexed by name

coefNames() - Method in class hex.FrameTask.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.DeepLearningV2.DeepLearningParametersV2

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

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.GLMLambdaTask

compute2() - Method in class hex.glm.LSMSolver.ADMMSolver.ParallelSolver

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

computeAIC() - Method in class hex.glm.GLMValidation

computeAUC() - Method in class hex.glm.GLMValidation

computeEta(int, int[], double[], double[]) - Method in class hex.glm.GLMTask

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() - Method in class hex.glm.LSMSolver

copyOver(WordCountTask) - Method in class hex.word2vec.WordCountTask

cos_sim - Variable in class hex.schemas.SynonymV1

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

CoxPHModelV2 - Class in hex.schemas

CoxPHModelV2() - Constructor for class hex.schemas.CoxPHModelV2

CoxPHModelV2.CoxPHModelOutputV2 - Class in hex.schemas

CoxPHModelV2.CoxPHModelOutputV2() - Constructor for class hex.schemas.CoxPHModelV2.CoxPHModelOutputV2

CoxPHV2 - Class in hex.schemas

CoxPHV2() - Constructor for class hex.schemas.CoxPHV2

CoxPHV2.CoxPHParametersV2 - Class in hex.schemas

CoxPHV2.CoxPHParametersV2() - Constructor for class hex.schemas.CoxPHV2.CoxPHParametersV2

createImpl() - Method in class hex.schemas.CoxPHModelV2

createImpl() - Method in class hex.schemas.CoxPHV2.CoxPHParametersV2

createImpl() - Method in class hex.schemas.DeepLearningModelV2

createImpl() - Method in class hex.schemas.GBMModelV2

createImpl() - Method in class hex.schemas.GLMModelV2

createImpl() - Method in class hex.schemas.GrepModelV2

createImpl() - Method in class hex.schemas.GrepModelV2.GrepModelOutputV2

createImpl() - Method in class hex.schemas.KMeansModelV2

createImpl() - Method in class hex.schemas.PCAModelV2

createImpl() - Method in class hex.schemas.QuantileModelV2

createImpl() - Method in class hex.schemas.QuantileModelV2.QuantileModelOutputV2

createImpl() - Method in class hex.schemas.SplitFrameModelV2

createImpl() - Method in class hex.schemas.SplitFrameModelV2.SplitFrameModelOutputV2

createImpl() - Method in class hex.schemas.Word2VecModelV2

createOutputSchema() - Method in class hex.schemas.CoxPHModelV2

createOutputSchema() - Method in class hex.schemas.DeepLearningModelV2

createOutputSchema() - Method in class hex.schemas.ExampleModelV2

createOutputSchema() - Method in class hex.schemas.GBMModelV2

createOutputSchema() - Method in class hex.schemas.GLMModelV2

createOutputSchema() - Method in class hex.schemas.GrepModelV2

createOutputSchema() - Method in class hex.schemas.KMeansModelV2

createOutputSchema() - Method in class hex.schemas.PCAModelV2

createOutputSchema() - Method in class hex.schemas.QuantileModelV2

createOutputSchema() - Method in class hex.schemas.SplitFrameModelV2

createOutputSchema() - Method in class hex.schemas.Word2VecModelV2

createParametersSchema() - Method in class hex.schemas.CoxPHModelV2

createParametersSchema() - Method in class hex.schemas.DeepLearningModelV2

createParametersSchema() - Method in class hex.schemas.ExampleModelV2

createParametersSchema() - Method in class hex.schemas.GBMModelV2

createParametersSchema() - Method in class hex.schemas.GLMModelV2

createParametersSchema() - Method in class hex.schemas.GrepModelV2

createParametersSchema() - Method in class hex.schemas.KMeansModelV2

createParametersSchema() - Method in class hex.schemas.PCAModelV2

createParametersSchema() - Method in class hex.schemas.QuantileModelV2

createParametersSchema() - Method in class hex.schemas.SplitFrameModelV2

createParametersSchema() - Method in class hex.schemas.Word2VecModelV2

cumVar - Variable in class hex.schemas.PCAModelV2.PCAModelOutputV2

D

data_info() - Method in class hex.deeplearning.DeepLearningModel.DeepLearningModelInfo

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

DBinomHistogram - Class in hex.tree

A Histogram, computed in parallel over a Vec.

DBinomHistogram(String, int, byte, float, float, long, boolean) - 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

decompTime - Variable in class hex.glm.LSMSolver.ADMMSolver

deep_clone() - Method in class hex.FrameTask.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

DeepLearningHandler - Class in hex.schemas

Deprecated.

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

Deprecated.

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, boolean, FrameTask.DataInfo) - Constructor for class hex.deeplearning.DeepLearningModel

Constructor to restart from a checkpointed model

DeepLearningModel(Key, DeepLearningModel.DeepLearningParameters, DeepLearningModel.DeepLearningOutput, 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, FrameTask.DataInfo, boolean, Frame, Frame) - Constructor for class hex.deeplearning.DeepLearningModel.DeepLearningModelInfo

DeepLearningModel.DeepLearningOutput - Class in hex.deeplearning

DeepLearningModel.DeepLearningOutput() - Constructor for class hex.deeplearning.DeepLearningModel.DeepLearningOutput

DeepLearningModel.DeepLearningOutput(DeepLearning) - Constructor for class hex.deeplearning.DeepLearningModel.DeepLearningOutput

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 CrossEntropy is recommended

DeepLearningModel.DeepLearningParameters.MissingValuesHandling - Enum in hex.deeplearning

DeepLearningModel.Errors - Class in hex.deeplearning

DeepLearningModel.Errors() - Constructor for class hex.deeplearning.DeepLearningModel.Errors

DeepLearningModelV2 - Class in hex.schemas

DeepLearningModelV2() - Constructor for class hex.schemas.DeepLearningModelV2

DeepLearningModelV2.DeepLearningModelOutputV2 - Class in hex.schemas

DeepLearningModelV2.DeepLearningModelOutputV2() - Constructor for class hex.schemas.DeepLearningModelV2.DeepLearningModelOutputV2

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

DeepLearningV2 - Class in hex.schemas

DeepLearningV2() - Constructor for class hex.schemas.DeepLearningV2

DeepLearningV2.DeepLearningParametersV2 - Class in hex.schemas

DeepLearningV2.DeepLearningParametersV2() - Constructor for class hex.schemas.DeepLearningV2.DeepLearningParametersV2

DEFAULT_ALPHA - Static variable in class hex.glm.LSMSolver.ADMMSolver

defaultLink - Variable in enum hex.glm.GLMModel.GLMParameters.Family

delete() - Method in class hex.word2vec.Word2VecModel

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

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

destKeys - Variable in class hex.schemas.SplitFrameV2.SplitFrameParametersV2

deviance(double, double) - Method in class hex.glm.GLMModel.GLMParameters

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, byte, float, float, long, boolean) - 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.DeepLearningV2.DeepLearningParametersV2

Gather diagnostics for hidden layers, such as mean and RMS values of learning rate, momentum, weights and biases.

dinfo() - Method in class hex.FrameTask

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

doScoringAndSaveModel(boolean, boolean, boolean) - Method in class hex.tree.SharedTree

doVarImpCalc(boolean) - Method in class hex.tree.gbm.GBM

doVarImpCalc(boolean) - Method in class hex.tree.SharedTree

DRealHistogram - Class in hex.tree

A Histogram, computed in parallel over a Vec.

DRealHistogram(String, int, byte, float, float, long, boolean) - Constructor for class hex.tree.DRealHistogram

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, int) - Constructor for class hex.tree.DTree

DTree(String[], int, 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, 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

eigVec - Variable in class hex.schemas.PCAModelV2.PCAModelOutputV2

end() - Method in class hex.deeplearning.Neurons.SparseVector

epoch_counter - Variable in class hex.deeplearning.DeepLearningModel

epoch_counter - Variable in class hex.deeplearning.DeepLearningModel.Errors

epochs - Variable in class hex.schemas.DeepLearningV2.DeepLearningParametersV2

The number of passes over the training dataset to be carried out.

epochs - Variable in class hex.schemas.Word2VecV2.Word2VecParametersV2

epsilon - Variable in class hex.schemas.DeepLearningV2.DeepLearningParametersV2

The second of two hyper parameters for adaptive learning rate (ADADELTA).

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

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

ExampleHandler - Class in hex.schemas

Deprecated.

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

Deprecated.

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

ExampleModelV2 - Class in hex.schemas

ExampleModelV2() - Constructor for class hex.schemas.ExampleModelV2

ExampleModelV2.ExampleModelOutputV2 - Class in hex.schemas

ExampleModelV2.ExampleModelOutputV2() - Constructor for class hex.schemas.ExampleModelV2.ExampleModelOutputV2

ExampleV2 - Class in hex.schemas

ExampleV2() - Constructor for class hex.schemas.ExampleV2

ExampleV2.ExampleParametersV2 - Class in hex.schemas

ExampleV2.ExampleParametersV2() - Constructor for class hex.schemas.ExampleV2.ExampleParametersV2

expert_mode - Variable in class hex.schemas.DeepLearningV2.DeepLearningParametersV2

Unlock expert mode parameters than can affect model building speed, predictive accuracy and scoring.

F

family - Variable in class hex.schemas.GLMV2.GLMParametersV2

fast_mode - Variable in class hex.schemas.DeepLearningV2.DeepLearningParametersV2

Enable fast mode (minor approximation in back-propagation), should not affect results significantly.

fillBytes(long) - Method in class hex.deeplearning.Dropout

fillFromImpl(GBMModel.GBMParameters) - Method in class hex.schemas.GBMV2.GBMParametersV2

fillFromImpl(GLMModel.GLMOutput) - Method in class hex.schemas.GLMModelV2.GLMModelOutputV2

fillFromImpl(GrepModel) - Method in class hex.schemas.GrepModelV2

fillFromImpl(GrepModel.GrepOutput) - Method in class hex.schemas.GrepModelV2.GrepModelOutputV2

fillFromImpl(KMeansModel.KMeansParameters) - Method in class hex.schemas.KMeansV2.KMeansParametersV2

fillFromImpl(QuantileModel) - Method in class hex.schemas.QuantileModelV2

fillFromImpl(QuantileModel.QuantileOutput) - Method in class hex.schemas.QuantileModelV2.QuantileModelOutputV2

fillFromImpl(SharedTreeModel.SharedTreeParameters) - Method in class hex.schemas.SharedTreeV2.SharedTreeParametersV2

fillFromImpl(SplitFrameModel) - Method in class hex.schemas.SplitFrameModelV2

fillFromImpl(SplitFrameModel.SplitFrameOutput) - Method in class hex.schemas.SplitFrameModelV2.SplitFrameModelOutputV2

fillImpl(GBMModel.GBMParameters) - Method in class hex.schemas.GBMV2.GBMParametersV2

fillImpl(KMeansModel.KMeansParameters) - Method in class hex.schemas.KMeansV2.KMeansParametersV2

filterExpandedColumns(int[]) - Method in class hex.FrameTask.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(int, SynonymV1) - Method in class hex.schemas.SynonymsHandler

Synonym: A process in which information is successively passed on.

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.DeepLearningV2.DeepLearningParametersV2

Increase training speed on small datasets by splitting it into many chunks to allow utilization of all cores.

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, FrameTask.DataInfo) - Constructor for class hex.FrameTask

FrameTask(Key, FrameTask.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

FrameTask.DataInfo - Class in hex

FrameTask.DataInfo(Key, Frame, Frame, int, boolean, double[], double[], FrameTask.DataInfo.TransformType, double[], double[]) - Constructor for class hex.FrameTask.DataInfo

FrameTask.DataInfo(Key, Frame, Frame, int, boolean, FrameTask.DataInfo.TransformType) - Constructor for class hex.FrameTask.DataInfo

FrameTask.DataInfo(Key, Frame, int[][], int, FrameTask.DataInfo.TransformType, FrameTask.DataInfo.TransformType, int, int) - Constructor for class hex.FrameTask.DataInfo

FrameTask.DataInfo(Key, Frame, Frame, int, boolean, FrameTask.DataInfo.TransformType, FrameTask.DataInfo.TransformType) - Constructor for class hex.FrameTask.DataInfo

FrameTask.DataInfo.TransformType - Enum in hex

fullN() - Method in class hex.FrameTask.DataInfo

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

G

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

GBMHandler - Class in hex.schemas

Deprecated.

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

Deprecated.

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.

GBMModelV2 - Class in hex.schemas

GBMModelV2() - Constructor for class hex.schemas.GBMModelV2

GBMModelV2.GBMModelOutputV2 - Class in hex.schemas

GBMModelV2.GBMModelOutputV2() - Constructor for class hex.schemas.GBMModelV2.GBMModelOutputV2

GBMV2 - Class in hex.schemas

GBMV2() - Constructor for class hex.schemas.GBMV2

GBMV2.GBMParametersV2 - Class in hex.schemas

GBMV2.GBMParametersV2() - Constructor for class hex.schemas.GBMV2.GBMParametersV2

gerr - Variable in class hex.glm.LSMSolver.ADMMSolver

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_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_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

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

getFold(int, int) - Method in class hex.FrameTask.DataInfo

getGloballyProcessed() - Method in class hex.word2vec.Word2VecModel.Word2VecModelInfo

getGradient(double[][]) - Method in class hex.glm.GLM.GLMGradientSolver

getGradient(double[][]) - Method in class hex.optimization.L_BFGS.GradientSolver

getGradient(double[]) - Method in class hex.optimization.L_BFGS.GradientSolver

getL() - Method in class hex.gram.Gram.InPlaceCholesky

getLocallyProcessed() - Method in class hex.word2vec.Word2VecModel.Word2VecModelInfo

getModelCategory() - Method in class hex.deeplearning.DeepLearningModel.DeepLearningOutput

getModelCategory() - Method in class hex.example.ExampleModel.ExampleOutput

getModelCategory() - Method in class hex.grep.GrepModel.GrepOutput

getModelCategory() - Method in class hex.kmeans.KMeansModel.KMeansOutput

getModelCategory() - Method in class hex.pca.PCAModel.PCAOutput

getModelCategory() - Method in class hex.quantile.QuantileModel.QuantileOutput

getModelCategory() - Method in class hex.splitframe.SplitFrameModel.SplitFrameOutput

getModelCategory() - Method in class hex.word2vec.Word2VecModel.Word2VecOutput

getModelInfo() - Method in class hex.word2vec.Word2VecModel

getModelInfo() - Method in class hex.word2vec.WordVectorTrainer

getParams() - Method in class hex.word2vec.Word2VecModel.Word2VecModelInfo

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.GLMDriver - Class in hex.glm

Contains implementation of the glm algo.

GLM.GLMDriver(H2O.H2OCountedCompleter, FrameTask.DataInfo) - Constructor for class hex.glm.GLM.GLMDriver

GLM.GLMGradientInfo - Class in hex.glm

GLM.GLMGradientInfo(GLMTask.GLMIterationTask, double) - Constructor for class hex.glm.GLM.GLMGradientInfo

GLM.GLMGradientSolver - Class in hex.glm

GLM.GLMGradientSolver(GLMModel.GLMParameters, FrameTask.DataInfo, double, double, long) - Constructor for class hex.glm.GLM.GLMGradientSolver

GLM.GLMLambdaTask - Class in hex.glm

Task to compute GLM solution for a particular (single) lambda value.

GLM.GLMLambdaTask(H2O.H2OCountedCompleter, Key, Key, GLM.GLMTaskInfo, double, boolean) - Constructor for class hex.glm.GLM.GLMLambdaTask

GLM.GLMTaskInfo - Class in hex.glm

Encapsulates state of the computation.

GLM.GLMTaskInfo(Key, FrameTask.DataInfo, GLMModel.GLMParameters, long, double, double, double, double[], double[], double) - Constructor for class hex.glm.GLM.GLMTaskInfo

GLMBuilderHandler - Class in hex.api

GLMBuilderHandler() - Constructor for class hex.api.GLMBuilderHandler

GLMHandler - Class in hex.schemas

Deprecated.

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

Deprecated.

GLMModel - Class in hex.glm

Created by tomasnykodym on 8/27/14.

GLMModel(Key, GLMModel.GLMParameters, GLMModel.GLMOutput, FrameTask.DataInfo, double, double, long) - Constructor for class hex.glm.GLMModel

GLMModel.GetScoringModelTask - Class in hex.glm

GLMModel.GetScoringModelTask(H2O.H2OCountedCompleter, Key, double) - Constructor for class hex.glm.GLMModel.GetScoringModelTask

GLMModel.GLM_LBFGS_Parameters - Class in hex.glm

GLMModel.GLM_LBFGS_Parameters() - Constructor for class hex.glm.GLMModel.GLM_LBFGS_Parameters

GLMModel.GLMOutput - Class in hex.glm

GLMModel.GLMOutput() - Constructor for class hex.glm.GLMModel.GLMOutput

GLMModel.GLMOutput(SupervisedModelBuilder, FrameTask.DataInfo, boolean) - 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[], double[], long, int, boolean) - Constructor for class hex.glm.GLMModel.Submodel

GLMModelV2 - Class in hex.schemas

GLMModelV2() - Constructor for class hex.schemas.GLMModelV2

GLMModelV2.GLMModelOutputV2 - Class in hex.schemas

GLMModelV2.GLMModelOutputV2() - Constructor for class hex.schemas.GLMModelV2.GLMModelOutputV2

GLMTask<T extends GLMTask<T>> - Class in hex.glm

Contains all GLM related distributed tasks.

GLMTask(Key, FrameTask.DataInfo, GLMModel.GLMParameters) - Constructor for class hex.glm.GLMTask

GLMTask(Key, FrameTask.DataInfo, GLMModel.GLMParameters, H2O.H2OCountedCompleter) - Constructor for class hex.glm.GLMTask

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, FrameTask.DataInfo, GLMModel.GLMParameters, boolean, boolean, boolean, double[], double, double, float[], H2O.H2OCountedCompleter) - Constructor for class hex.glm.GLMTask.GLMIterationTask

GLMTask.GLMLineSearchTask - Class in hex.glm

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

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

GLMTask.GLMValidationTask<T extends GLMTask.GLMValidationTask<T>> - Class in hex.glm

GLMTask.GLMValidationTask(GLMModel, double) - Constructor for class hex.glm.GLMTask.GLMValidationTask

GLMTask.GLMValidationTask(GLMModel, double, H2O.H2OCountedCompleter) - Constructor for class hex.glm.GLMTask.GLMValidationTask

GLMTask.GLMXValidationTask - Class in hex.glm

GLMTask.GLMXValidationTask(GLMModel, double, GLMModel[], float[]) - Constructor for class hex.glm.GLMTask.GLMXValidationTask

GLMTask.GLMXValidationTask(GLMModel, double, GLMModel[], float[], H2O.H2OCountedCompleter) - Constructor for class hex.glm.GLMTask.GLMXValidationTask

GLMV2 - Class in hex.schemas

Created by tomasnykodym on 8/29/14.

GLMV2() - Constructor for class hex.schemas.GLMV2

GLMV2.GLMParametersV2 - Class in hex.schemas

GLMV2.GLMParametersV2() - Constructor for class hex.schemas.GLMV2.GLMParametersV2

GLMValidation - Class in hex.glm

Class for GLMValidation.

GLMValidation(Key, double, GLMModel.GLMParameters, int) - Constructor for class hex.glm.GLMValidation

GLMValidation(Key, double, GLMModel.GLMParameters, int, float[]) - Constructor for class hex.glm.GLMValidation

GLMValidation.GLMXValidation - Class in hex.glm

GLMValidation.GLMXValidation(GLMModel, GLMModel[], GLMValidation[], double, long, float[]) - Constructor for class hex.glm.GLMValidation.GLMXValidation

GLMValidationTsk - Class in hex.glm

Created by tomasnykodym on 9/12/14.

GLMValidationTsk(GLMModel.GLMParameters, double, int) - Constructor for class hex.glm.GLMValidationTsk

grad(Gram, double[], double[]) - Method in class hex.glm.LSMSolver

gradient(double, double) - Method in class hex.glm.GLMTask.GLMIterationTask

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.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, FrameTask.DataInfo, boolean, boolean) - 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

GrepHandler - Class in hex.schemas

Deprecated.

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

Deprecated.

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

GrepModelV2 - Class in hex.schemas

GrepModelV2() - Constructor for class hex.schemas.GrepModelV2

GrepModelV2.GrepModelOutputV2 - Class in hex.schemas

GrepModelV2.GrepModelOutputV2() - Constructor for class hex.schemas.GrepModelV2.GrepModelOutputV2

GrepV2 - Class in hex.schemas

GrepV2() - Constructor for class hex.schemas.GrepV2

GrepV2.GrepParametersV2 - Class in hex.schemas

GrepV2.GrepParametersV2() - Constructor for class hex.schemas.GrepV2.GrepParametersV2

group_split - Variable in class hex.schemas.GBMV2.GBMParametersV2

H

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

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.gram - package hex.gram

hex.grep - package hex.grep

hex.kmeans - package hex.kmeans

hex.optimization - package hex.optimization

hex.pca - package hex.pca

hex.quantile - package hex.quantile

hex.schemas - package hex.schemas

hex.splitframe - package hex.splitframe

hex.tree - package hex.tree

hex.tree.gbm - package hex.tree.gbm

hex.utils - package hex.utils

hex.word2vec - package hex.word2vec

hidden - Variable in class hex.schemas.DeepLearningV2.DeepLearningParametersV2

The number and size of each hidden layer in the model.

hidden_dropout_ratios - Variable in class hex.schemas.DeepLearningV2.DeepLearningParametersV2

A fraction of the inputs for each hidden layer to be omitted from training in order to improve generalization.

higher_accuracy - Variable in class hex.schemas.GLMV2.GLMParametersV2

I

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

ignore_const_cols - Variable in class hex.schemas.DeepLearningV2.DeepLearningParametersV2

Ignore constant training columns (no information can be gained anyway).

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.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.pca.PCA

init(boolean) - Method in class hex.quantile.Quantile

Initialize the ModelBuilder, validating all arguments and preparing the training frame.

init - Variable in class hex.schemas.KMeansV2.KMeansParametersV2

init(boolean) - Method in class hex.splitframe.SplitFrame

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.

initial_weight_distribution - Variable in class hex.schemas.DeepLearningV2.DeepLearningParametersV2

The distribution from which initial weights are to be drawn.

initial_weight_scale - Variable in class hex.schemas.DeepLearningV2.DeepLearningParametersV2

The scale of the distribution function for Uniform or Normal distributions.

initialHist(Frame, int, int, DHistogram[], boolean, boolean) - Static method in class hex.tree.DHistogram

initLearningRate - Variable in class hex.schemas.Word2VecV2.Word2VecParametersV2

initStats(CoxPHModel, FrameTask.DataInfo) - Method in class hex.coxph.CoxPH.CoxPHDriver

input_dropout_ratio - Variable in class hex.schemas.DeepLearningV2.DeepLearningParametersV2

A fraction of the features for each training row to be omitted from training in order to improve generalization (dimension sampling).

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

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

isSPD() - Method in class hex.gram.Gram.InPlaceCholesky

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

isSupervised() - Method in class hex.pca.PCAModel

isValid() - Method in class hex.tree.TreeStats

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

iter_max - Variable in class hex.coxph.CoxPHModel.CoxPHParameters

iterations - Variable in class hex.glm.LSMSolver.ADMMSolver

iters - Variable in class hex.schemas.ExampleModelV2.ExampleModelOutputV2

iters - Variable in class hex.schemas.KMeansModelV2.KMeansModelOutputV2

iters - Variable in class hex.schemas.QuantileModelV2.QuantileModelOutputV2

K

k - Variable in class hex.schemas.KMeansV2.KMeansParametersV2

keep_cross_validation_splits - Variable in class hex.schemas.DeepLearningV2.DeepLearningParametersV2

key - Variable in class hex.schemas.SynonymV1

KMeans - Class in hex.kmeans

Scalable K-Means++ (KMeans||)
http://theory.stanford.edu/~sergei/papers/vldb12-kmpar.pdf
http://www.youtube.com/watch?v=cigXAxV3XcY

KMeans(KMeansModel.KMeansParameters) - Constructor for class hex.kmeans.KMeans

KMeans.Initialization - Enum in hex.kmeans

KMeansBuilderHandler - Class in hex.api

KMeansBuilderHandler() - Constructor for class hex.api.KMeansBuilderHandler

KMeansHandler - Class in hex.schemas

Deprecated.

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

Deprecated.

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

KMeansModelV2 - Class in hex.schemas

KMeansModelV2() - Constructor for class hex.schemas.KMeansModelV2

KMeansModelV2.KMeansModelOutputV2 - Class in hex.schemas

KMeansModelV2.KMeansModelOutputV2() - Constructor for class hex.schemas.KMeansModelV2.KMeansModelOutputV2

KMeansV2 - Class in hex.schemas

KMeansV2() - Constructor for class hex.schemas.KMeansV2

KMeansV2.KMeansParametersV2 - Class in hex.schemas

KMeansV2.KMeansParametersV2() - Constructor for class hex.schemas.KMeansV2.KMeansParametersV2

L

l1 - Variable in class hex.schemas.DeepLearningV2.DeepLearningParametersV2

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[]) - Static method in class hex.glm.GLM

l2 - Variable in class hex.schemas.DeepLearningV2.DeepLearningParametersV2

A regularization method that constrdains the sum of the squared weights.

l2norm(double[]) - Static method in class hex.glm.GLM

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

To be overriden to provide gradient computation specific for 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.L_BFGS_Params - Class in hex.optimization

Internal parameters affecting behavior of L-BFGS solver.

L_BFGS.L_BFGS_Params() - Constructor for class hex.optimization.L_BFGS.L_BFGS_Params

L_BFGS.Result - Class in hex.optimization

L_BFGS.Result(int, double[], L_BFGS.GradientInfo) - Constructor for class hex.optimization.L_BFGS.Result

lambda - Variable in class hex.schemas.GLMV2.GLMParametersV2

lambda_min_ratio - Variable in class hex.schemas.GLMV2.GLMParametersV2

lambda_search - Variable in class hex.schemas.GLMV2.GLMParametersV2

largestCat() - Method in class hex.FrameTask.DataInfo

leaf(float) - Method in class hex.tree.TreeVisitor

learn_rate - Variable in class hex.schemas.GBMV2.GBMParametersV2

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

link(double) - Method in class hex.glm.GLMModel.GLMParameters

link - Variable in class hex.schemas.GLMV2.GLMParametersV2

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

loss - Variable in class hex.schemas.DeepLearningV2.DeepLearningParametersV2

The loss (error) function to be minimized by the model.

loss - Variable in class hex.schemas.GBMV2.GBMParametersV2

lre_min - Variable in class hex.coxph.CoxPHModel.CoxPHParameters

lsm_objectiveVal(double[], double, double[], double[]) - Method in class hex.glm.LSMSolver

Compute the LSM objective.

LSMSolver - Class in hex.glm

Distributed least squares solvers

LSMSolver(double, double) - Constructor for class hex.glm.LSMSolver

LSMSolver.ADMMSolver - Class in hex.glm

LSMSolver.ADMMSolver(double, double, double) - Constructor for class hex.glm.LSMSolver.ADMMSolver

LSMSolver.ADMMSolver(double, double, double, double) - Constructor for class hex.glm.LSMSolver.ADMMSolver

LSMSolver.ADMMSolver.NonSPDMatrixException - Exception in hex.glm

LSMSolver.ADMMSolver.NonSPDMatrixException() - Constructor for exception hex.glm.LSMSolver.ADMMSolver.NonSPDMatrixException

LSMSolver.ADMMSolver.NonSPDMatrixException(Gram) - Constructor for exception hex.glm.LSMSolver.ADMMSolver.NonSPDMatrixException

LSMSolver.ADMMSolver.ParallelSolver - Class in hex.glm

LSMSolver.LSMSolverException - Exception in hex.glm

LSMSolver.LSMSolverException(String) - Constructor for exception hex.glm.LSMSolver.LSMSolverException

LSMSolver.LSMSolverType - Enum in hex.glm

LSMSolver.ProxSolver - Class in hex.glm

LSMSolver.ProxSolver(double, double) - Constructor for class hex.glm.LSMSolver.ProxSolver

M

make(String, int, byte, float, float, long, boolean, boolean) - Static method in class hex.tree.DHistogram

makeDecided(DTree.UndecidedNode, DHistogram[]) - Method in class hex.tree.gbm.GBM

makeDecided(DTree.UndecidedNode, DHistogram[]) - Method in class hex.tree.SharedTree

makeKey() - Static method in class hex.glm.GLMTask.GLMValidationTask

makeKey() - Static method in class hex.glm.GLMTask.GLMXValidationTask

makeKey() - Static method in class hex.glm.GLMValidation

makeModel(Key, P, double, double) - Method in class hex.tree.SharedTree.Driver

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

map(Chunk[]) - Method in class hex.glm.GLMTask.GLMValidationTask

map(Chunk[]) - Method in class hex.glm.GLMTask.GLMXValidationTask

map(Chunk, Chunk) - Method in class hex.glm.GLMValidationTsk

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, Chunk) - Method in class hex.utils.MSETsk

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

matches - Variable in class hex.schemas.GrepModelV2.GrepModelOutputV2

max_categorical_features - Variable in class hex.schemas.DeepLearningV2.DeepLearningParametersV2

max_confusion_matrix_size - Variable in class hex.schemas.DeepLearningV2.DeepLearningParametersV2

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.GBMV2.GBMParametersV2

max_hit_ratio_k - Variable in class hex.schemas.DeepLearningV2.DeepLearningParametersV2

The maximum number (top K) of predictions to use for hit ratio computation (for multi-class only, 0 to disable)

max_iters - Variable in class hex.schemas.ExampleV2.ExampleParametersV2

max_iters - Variable in class hex.schemas.KMeansV2.KMeansParametersV2

max_pc - Variable in class hex.schemas.PCAV2.PCAParametersV2

max_ver() - Method in class hex.schemas.DeepLearningHandler

Deprecated.

max_ver() - Method in class hex.schemas.ExampleHandler

Deprecated.

max_ver() - Method in class hex.schemas.GBMHandler

Deprecated.

max_ver() - Method in class hex.schemas.GLMHandler

Deprecated.

max_ver() - Method in class hex.schemas.GrepHandler

Deprecated.

max_ver() - Method in class hex.schemas.KMeansHandler

Deprecated.

max_ver() - Method in class hex.schemas.QuantileHandler

Deprecated.

max_ver() - Method in class hex.schemas.SplitFrameHandler

Deprecated.

max_ver() - Method in class hex.schemas.SynonymsHandler

max_ver() - Method in class hex.schemas.Word2VecHandler

Deprecated.

max_w2 - Variable in class hex.schemas.DeepLearningV2.DeepLearningParametersV2

A maximum on the sum of the squared incoming weights into any one neuron.

maxs - Variable in class hex.schemas.ExampleModelV2.ExampleModelOutputV2

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

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

mid(int, float, int) - Method in class hex.tree.TreeVisitor

min_rows - Variable in class hex.schemas.GBMV2.GBMParametersV2

min_ver() - Method in class hex.schemas.DeepLearningHandler

Deprecated.

min_ver() - Method in class hex.schemas.ExampleHandler

Deprecated.

min_ver() - Method in class hex.schemas.GBMHandler

Deprecated.

min_ver() - Method in class hex.schemas.GLMHandler

Deprecated.

min_ver() - Method in class hex.schemas.GrepHandler

Deprecated.

min_ver() - Method in class hex.schemas.KMeansHandler

Deprecated.

min_ver() - Method in class hex.schemas.QuantileHandler

Deprecated.

min_ver() - Method in class hex.schemas.SplitFrameHandler

Deprecated.

min_ver() - Method in class hex.schemas.SynonymsHandler

min_ver() - Method in class hex.schemas.Word2VecHandler

Deprecated.

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

minWordFreq - Variable in class hex.schemas.Word2VecV2.Word2VecParametersV2

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.DeepLearningV2.DeepLearningParametersV2

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

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)

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.DeepLearningV2.DeepLearningParametersV2

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.DeepLearningV2.DeepLearningParametersV2

The momentum_stable parameter controls the final momentum value reached after momentum_ramp training samples.

momentum_start - Variable in class hex.schemas.DeepLearningV2.DeepLearningParametersV2

The momentum_start parameter controls the amount of momentum at the beginning of training.

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

mse - Variable in class hex.schemas.SharedTreeModelV2.SharedTreeModelOutputV2

mse_train - Variable in class hex.schemas.GBMModelV2.GBMModelOutputV2

mse_train - Variable in class hex.schemas.SharedTreeV2.SharedTreeParametersV2

Train and validation errors per-tree (scored).

mse_valid - Variable in class hex.schemas.GBMModelV2.GBMModelOutputV2

mse_valid - Variable in class hex.schemas.SharedTreeV2.SharedTreeParametersV2

MSETsk - Class in hex.utils

Created by tomasnykodym on 9/9/14.

MSETsk() - Constructor for class hex.utils.MSETsk

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

mustart(double, double) - Method in class hex.glm.GLMModel.GLMParameters

N

n - Variable in class hex.coxph.CoxPH.CoxPHTask

n_folds - Variable in class hex.schemas.DeepLearningV2.DeepLearningParametersV2

n_folds - Variable in class hex.schemas.GLMV2.GLMParametersV2

n_missing - Variable in class hex.coxph.CoxPH.CoxPHTask

N_THRESHOLDS - Static variable in class hex.glm.GLMTask.GLMIterationTask

name() - Method in class hex.glm.LSMSolver.ADMMSolver

name() - Method in class hex.glm.LSMSolver

name() - Method in class hex.glm.LSMSolver.ProxSolver

namesExp - Variable in class hex.schemas.PCAModelV2.PCAModelOutputV2

nbins - Variable in class hex.schemas.GBMV2.GBMParametersV2

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

ncats - Variable in class hex.schemas.KMeansModelV2.KMeansModelOutputV2

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

needLineSearch(GLMTask.GLMIterationTask) - Method in class hex.glm.GLM.GLMLambdaTask

needLineSearch(GLMTask.GLMIterationTask, double) - Method in class hex.glm.GLM.GLMLambdaTask

needLineSearch(double[], double, double) - Method in class hex.glm.GLM.GLMLambdaTask

negSampleCnt - Variable in class hex.schemas.Word2VecV2.Word2VecParametersV2

nesterov_accelerated_gradient - Variable in class hex.schemas.DeepLearningV2.DeepLearningParametersV2

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 - Softmax

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

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.GLMV2.GLMParametersV2

nnz() - Method in class hex.deeplearning.Neurons.SparseVector

node(int) - Method in class hex.tree.DTree

normalize() - Method in class hex.glm.LSMSolver.ADMMSolver

normModel - Variable in class hex.schemas.Word2VecV2.Word2VecParametersV2

normMul - Variable in class hex.schemas.PCAModelV2.PCAModelOutputV2

normSub - Variable in class hex.schemas.PCAModelV2.PCAModelOutputV2

ns(Chunk[], int) - Method in class hex.tree.DTree.DecidedNode

ntrees - Variable in class hex.schemas.GBMV2.GBMParametersV2

ntrees - Variable in class hex.schemas.SharedTreeV2.SharedTreeParametersV2

Number of trees in model

ntrees() - Method in class hex.tree.DTreeScorer

nullDeviance() - Method in class hex.glm.GLMValidation

nullDOF() - Method in class hex.glm.GLMValidation

nullModelBeta(FrameTask.DataInfo, double) - Method in class hex.glm.GLMModel.GLMParameters

num_pc - Variable in class hex.schemas.PCAModelV2.PCAModelOutputV2

numStart() - Method in class hex.FrameTask.DataInfo

O

objectiveVal(double[], double, double[], double[]) - Method in class hex.glm.LSMSolver

Compute least squares objective function value: lsm_obj(beta) = 0.5*(y - X*b)'*(y - X*b) + l1 + l2 = 0.5*y'y - (X'y)'*b + 0.5*b'*X'X*b) + l1 + l2 l1 = alpha*lambda_value*l1norm(beta) l2 = (1-alpha)*lambda_value*l2norm(beta)/2

offset_columns - Variable in class hex.coxph.CoxPHModel.CoxPHParameters

offsets - Variable in class hex.schemas.GrepModelV2.GrepModelOutputV2

onCompletion(CountedCompleter) - Method in class hex.glm.GLM.GLMDriver

onCompletion(CountedCompleter) - Method in class hex.glm.LSMSolver.ADMMSolver.ParallelSolver

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

override_with_best_model - Variable in class hex.schemas.DeepLearningV2.DeepLearningParametersV2

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.CoxPHV2.CoxPHParametersV2

own_fields - Static variable in class hex.schemas.DeepLearningV2.DeepLearningParametersV2

own_fields - Static variable in class hex.schemas.ExampleV2.ExampleParametersV2

own_fields - Static variable in class hex.schemas.GBMV2.GBMParametersV2

own_fields - Static variable in class hex.schemas.GLMV2.GLMParametersV2

own_fields - Static variable in class hex.schemas.GrepV2.GrepParametersV2

own_fields - Static variable in class hex.schemas.KMeansV2.KMeansParametersV2

own_fields - Static variable in class hex.schemas.PCAV2.PCAParametersV2

own_fields - Static variable in class hex.schemas.QuantileV2.QuantileParametersV2

own_fields - Static variable in class hex.schemas.SharedTreeV2.SharedTreeParametersV2

own_fields - Static variable in class hex.schemas.SplitFrameV2.SplitFrameParametersV2

own_fields - Static variable in class hex.schemas.Word2VecV2.Word2VecParametersV2

P

params - Variable in class hex.deeplearning.Neurons

Parameters (deep-cloned() from the user input, can be modified here, e.g.

parSolver(Gram, double[], double[], double, int, int) - Method in class hex.glm.LSMSolver.ADMMSolver

parSolver(CountedCompleter, double[], int, int) - Method in class hex.gram.Gram.Cholesky

PCA - Class in hex.pca

Principal Components Analysis This is an algorithm for dimensionality reduction of numerical data.

PCA(PCAModel.PCAParameters) - Constructor for class hex.pca.PCA

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

PCAModelV2 - Class in hex.schemas

PCAModelV2() - Constructor for class hex.schemas.PCAModelV2

PCAModelV2.PCAModelOutputV2 - Class in hex.schemas

PCAModelV2.PCAModelOutputV2() - Constructor for class hex.schemas.PCAModelV2.PCAModelOutputV2

PCAV2 - Class in hex.schemas

PCAV2() - Constructor for class hex.schemas.PCAV2

PCAV2.PCAParametersV2 - Class in hex.schemas

PCAV2.PCAParametersV2() - Constructor for class hex.schemas.PCAV2.PCAParametersV2

pickBestModel(boolean) - Method in class hex.glm.GLMModel.GLMOutput

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.glm.GLMTask.GLMLineSearchTask

postGlobal() - Method in class hex.glm.GLMTask.GLMValidationTask

postGlobal() - Method in class hex.glm.GLMTask.GLMXValidationTask

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

pre(int, float, IcedBitSet, int) - Method in class hex.tree.TreeVisitor

printGenerateTrees(DTree[]) - Static method in class hex.tree.SharedTree

prior1 - Variable in class hex.schemas.GLMV2.GLMParametersV2

probs - Variable in class hex.schemas.QuantileV2.QuantileParametersV2

processRow(long, double[], int, int[], double[]) - Method in class hex.coxph.CoxPH.CoxPHTask

processRow(long, double[], int, int[], double[]) - Method in class hex.deeplearning.DeepLearningTask

processRow(long, double[], int, int[], double[]) - Method in class hex.FrameTask

Method to process one row of the data for GLM functions.

processRow(long, double[], int, int[], double[], NewChunk[]) - Method in class hex.FrameTask

processRow(long, double[], int, int[], double[]) - Method in class hex.glm.GLMTask.GLMIterationTask

processRow(long, double[], int, int[], double[]) - Method in class hex.glm.GLMTask.GLMLineSearchTask

processRow(long, double[], int, int[], double[]) - Method in class hex.gram.Gram.GramTask

propVar - Variable in class hex.schemas.PCAModelV2.PCAModelOutputV2

Q

Quantile - Class in hex.quantile

Quantile model builder...

Quantile(QuantileModel.QuantileParameters) - Constructor for class hex.quantile.Quantile

QuantileBuilderHandler - Class in hex.api

QuantileBuilderHandler() - Constructor for class hex.api.QuantileBuilderHandler

QuantileHandler - Class in hex.schemas

Deprecated.

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

Deprecated.

QuantileModel - Class in hex.quantile

QuantileModel.QuantileOutput - Class in hex.quantile

QuantileModel.QuantileOutput(Quantile) - Constructor for class hex.quantile.QuantileModel.QuantileOutput

QuantileModel.QuantileParameters - Class in hex.quantile

QuantileModel.QuantileParameters() - Constructor for class hex.quantile.QuantileModel.QuantileParameters

QuantileModelV2 - Class in hex.schemas

QuantileModelV2() - Constructor for class hex.schemas.QuantileModelV2

QuantileModelV2.QuantileModelOutputV2 - Class in hex.schemas

QuantileModelV2.QuantileModelOutputV2() - Constructor for class hex.schemas.QuantileModelV2.QuantileModelOutputV2

quantiles - Variable in class hex.schemas.QuantileModelV2.QuantileModelOutputV2

QuantileV2 - Class in hex.schemas

QuantileV2() - Constructor for class hex.schemas.QuantileV2

QuantileV2.QuantileParametersV2 - Class in hex.schemas

QuantileV2.QuantileParametersV2() - Constructor for class hex.schemas.QuantileV2.QuantileParametersV2

quiet_mode - Variable in class hex.schemas.DeepLearningV2.DeepLearningParametersV2

Enable quiet mode for less output to standard output.

R

r2 - Variable in class hex.schemas.SharedTreeV2.SharedTreeParametersV2

r2 metric on validation set: 1-(MSE(model) / MSE(mean))

randomlySparsifyActivation(Neurons.Vector, long) - Method in class hex.deeplearning.Dropout

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

rank(double) - Method in class hex.glm.GLMModel.GLMOutput

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

rank - Variable in class hex.schemas.PCAModelV2.PCAModelOutputV2

rate(long) - Method in class hex.deeplearning.Neurons

The learning rate

rate - Variable in class hex.schemas.DeepLearningV2.DeepLearningParametersV2

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.DeepLearningV2.DeepLearningParametersV2

Learning rate annealing reduces the learning rate to "freeze" into local minima in the optimization landscape.

rate_decay - Variable in class hex.schemas.DeepLearningV2.DeepLearningParametersV2

The learning rate decay parameter controls the change of learning rate across layers.

ratios - Variable in class hex.schemas.SplitFrameV2.SplitFrameParametersV2

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.

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

reduce(GLMTask.GLMLineSearchTask) - Method in class hex.glm.GLMTask.GLMLineSearchTask

reduce(GLMTask.GLMValidationTask) - Method in class hex.glm.GLMTask.GLMValidationTask

reduce(GLMTask.GLMXValidationTask) - Method in class hex.glm.GLMTask.GLMXValidationTask

reduce(GLMValidationTsk) - Method in class hex.glm.GLMValidationTsk

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

reduce(Score) - Method in class hex.tree.Score

reduce(ScoreBuildHistogram) - Method in class hex.tree.ScoreBuildHistogram

reduce(MSETsk) - Method in class hex.utils.MSETsk

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.GrepV2.GrepParametersV2

regression_stop - Variable in class hex.schemas.DeepLearningV2.DeepLearningParametersV2

The stopping criteria in terms of regression error (MSE) on the training data scoring dataset.

remove_impl(Futures) - Method in class hex.tree.SharedTreeModel

replicate_training_data - Variable in class hex.schemas.DeepLearningV2.DeepLearningParametersV2

Replicate the entire training dataset onto every node for faster training on small datasets.

reproducible - Variable in class hex.schemas.DeepLearningV2.DeepLearningParametersV2

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

rho - Variable in class hex.schemas.DeepLearningV2.DeepLearningParametersV2

The first of two hyper parameters for adaptive learning rate (ADADELTA).

rms_weight - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningModelInfo

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

S

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.example.ExampleModel

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

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

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

schema() - Method in class hex.grep.GrepModel

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

schema() - Method in class hex.kmeans.KMeansModel

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

schema() - Method in class hex.pca.PCAModel

schema() - Method in class hex.quantile.Quantile

schema() - Method in class hex.quantile.QuantileModel

schema() - Method in class hex.splitframe.SplitFrame

schema() - Method in class hex.splitframe.SplitFrameModel

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

schema() - Method in class hex.tree.gbm.GBMModel

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

schema() - Method in class hex.word2vec.Word2VecModel

score(Frame) - Method in class hex.deeplearning.DeepLearningModel

Score - Class in hex.tree

Score the tree columns, and produce a confusion matrix and AUC

Score(SharedTree, boolean) - Constructor for class hex.tree.Score

Compute ModelMetrics on the testing dataset.

score0(double[], float[]) - Method in class hex.coxph.CoxPHModel

Predict from raw double values representing the data

score0(double[], float[]) - Method in class hex.deeplearning.DeepLearningModel

Predict from raw double values representing the data

score0(double[], float[]) - Method in class hex.example.ExampleModel

score0(Chunk[], int, double[], float[]) - Method in class hex.glm.GLMModel

score0(double[], float[]) - Method in class hex.glm.GLMModel

score0(double[], float[]) - Method in class hex.grep.GrepModel

score0(double[], float[]) - Method in class hex.kmeans.KMeansModel

score0(double[], float[]) - Method in class hex.pca.PCAModel

score0(double[], float[]) - Method in class hex.quantile.QuantileModel

score0(double[], float[]) - Method in class hex.splitframe.SplitFrameModel

score0(double[], float[], CompressedTree[]) - Method in class hex.tree.DTreeScorer

score0(Chunk[], int, double[], float[]) - Method in class hex.tree.gbm.GBMModel

Bulk scoring API for one row.

score0(double[], float[]) - Method in class hex.tree.gbm.GBMModel

score0(double[], float[]) - Method in class hex.tree.SharedTreeModel

score0(double[], float[], int) - Method in class hex.tree.SharedTreeModel

score0(Chunk[], int, double[], float[]) - Method in class hex.word2vec.Word2VecModel

score0(double[], float[]) - Method in class hex.word2vec.Word2VecModel

score1(Chunk[], float[], int) - Method in class hex.tree.gbm.GBM

score1(Chunk[], float[], int) - Method in class hex.tree.SharedTree

score_duty_cycle - Variable in class hex.schemas.DeepLearningV2.DeepLearningParametersV2

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.DeepLearningV2.DeepLearningParametersV2

The minimum time (in seconds) to elapse between model scoring.

score_training_samples - Variable in class hex.deeplearning.DeepLearningModel.Errors

score_training_samples - Variable in class hex.schemas.DeepLearningV2.DeepLearningParametersV2

The number of training dataset points to be used for scoring.

score_validation_samples - Variable in class hex.deeplearning.DeepLearningModel.Errors

score_validation_samples - Variable in class hex.schemas.DeepLearningV2.DeepLearningParametersV2

The number of validation dataset points to be used for scoring.

score_validation_sampling - Variable in class hex.schemas.DeepLearningV2.DeepLearningParametersV2

Method used to sample the validation dataset for scoring, see Score Validation Samples above.

scoreAutoEncoder(Frame) - Method in class hex.deeplearning.DeepLearningModel

Score auto-encoded reconstruction (on-the-fly, without allocating the reconstruction as done in Frame score(Frame fr))

ScoreBuildHistogram - Class in hex.tree

Score and Build Histogram

ScoreBuildHistogram(H2O.H2OCountedCompleter, int, int, int, DTree, int, DHistogram[][], boolean) - Constructor for class hex.tree.ScoreBuildHistogram

scoreCols(DHistogram[]) - Method in class hex.tree.DTree.UndecidedNode

scoreImpl(Frame, Frame) - Method in class hex.deeplearning.DeepLearningModel

Make either a prediction or a reconstruction.

scoreMSE(int) - Method in class hex.tree.DBinomHistogram

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

scoreMSE(int) - Method in class hex.tree.DRealHistogram

scoreTree(double[], float[], 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.Errors

sdev - Variable in class hex.schemas.PCAModelV2.PCAModelOutputV2

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

seed - Variable in class hex.schemas.DeepLearningV2.DeepLearningParametersV2

The random seed controls sampling and initialization.

seed - Variable in class hex.schemas.GBMV2.GBMParametersV2

seed - Variable in class hex.schemas.KMeansV2.KMeansParametersV2

sentSampleRate - Variable in class hex.schemas.Word2VecV2.Word2VecParametersV2

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

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

setMax(float) - Method in class hex.tree.DHistogram

setMin(float) - Method in class hex.tree.DHistogram

setModelBuilderTrain(Frame) - Method in class hex.coxph.CoxPH.CoxPHDriver

setNumTrees(int) - Method in class hex.tree.TreeStats

setSPD(boolean) - Method in class hex.gram.Gram.Cholesky

setSubmodel(H2O.H2OCountedCompleter, Key, double, double[], double[], int, long, boolean, GLMValidation) - Static 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.glm.GLMTask.GLMLineSearchTask

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

setXvalidation(H2O.H2OCountedCompleter, Key, double, GLMValidation) - Static method in class hex.glm.GLMModel

SharedTree<M extends SharedTreeModel<M,P,O>,P extends SharedTreeModel.SharedTreeParameters,O extends SharedTreeModel.SharedTreeOutput> - Class in hex.tree

SharedTree(String, P) - Constructor for class hex.tree.SharedTree

SharedTree.Driver - Class in hex.tree

SharedTree.Driver() - Constructor for class hex.tree.SharedTree.Driver

SharedTreeHandler - Class in hex.schemas

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

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

SharedTreeModelV2 - Class in hex.schemas

SharedTreeModelV2() - Constructor for class hex.schemas.SharedTreeModelV2

SharedTreeModelV2.SharedTreeModelOutputV2 - Class in hex.schemas

SharedTreeModelV2.SharedTreeModelOutputV2() - Constructor for class hex.schemas.SharedTreeModelV2.SharedTreeModelOutputV2

SharedTreeV2 - Class in hex.schemas

SharedTreeV2() - Constructor for class hex.schemas.SharedTreeV2

SharedTreeV2.SharedTreeParametersV2 - Class in hex.schemas

SharedTreeV2.SharedTreeParametersV2() - Constructor for class hex.schemas.SharedTreeV2.SharedTreeParametersV2

shrinkage(double, double) - Static method in class hex.glm.LSMSolver

shuffle_training_data - Variable in class hex.schemas.DeepLearningV2.DeepLearningParametersV2

Enable shuffling of training data (on each node).

single_node_mode - Variable in class hex.schemas.DeepLearningV2.DeepLearningParametersV2

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 - Variable in class hex.schemas.KMeansModelV2.KMeansModelOutputV2

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

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

skipMissing() - Method in class hex.FrameTask

solve(Gram, double[], double, double[]) - Method in class hex.glm.LSMSolver.ADMMSolver

solve(Gram, double[], double, double[], double) - Method in class hex.glm.LSMSolver.ADMMSolver

solve(Gram, double[], double, double[]) - Method in class hex.glm.LSMSolver.ProxSolver

solve(Gram, double[], double, double[]) - Method in class hex.glm.LSMSolver

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

Find solution to A*x = y.

solve(int, L_BFGS.GradientSolver, L_BFGS.L_BFGS_Params) - Static 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, L_BFGS.L_BFGS_Params, L_BFGS.History, double[]) - Static 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.GLMV2.GLMParametersV2

sparse - Variable in class hex.schemas.DeepLearningV2.DeepLearningParametersV2

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

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

sparsity_beta - Variable in class hex.schemas.DeepLearningV2.DeepLearningParametersV2

split(int, char, int, DHistogram[], float) - Method in class hex.tree.DTree.Split

SplitFrame - Class in hex.splitframe

Frame splitter function to divide given frame into multiple partitions based on given ratios.

SplitFrame(SplitFrameModel.SplitFrameParameters) - Constructor for class hex.splitframe.SplitFrame

SplitFrameBuilderHandler - Class in hex.api

SplitFrameBuilderHandler() - Constructor for class hex.api.SplitFrameBuilderHandler

SplitFrameHandler - Class in hex.schemas

Deprecated.

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

Deprecated.

SplitFrameModel - Class in hex.splitframe

SplitFrameModel.SplitFrameOutput - Class in hex.splitframe

SplitFrameModel.SplitFrameOutput(SplitFrame) - Constructor for class hex.splitframe.SplitFrameModel.SplitFrameOutput

SplitFrameModel.SplitFrameParameters - Class in hex.splitframe

SplitFrameModel.SplitFrameParameters() - Constructor for class hex.splitframe.SplitFrameModel.SplitFrameParameters

SplitFrameModelV2 - Class in hex.schemas

SplitFrameModelV2() - Constructor for class hex.schemas.SplitFrameModelV2

SplitFrameModelV2.SplitFrameModelOutputV2 - Class in hex.schemas

SplitFrameModelV2.SplitFrameModelOutputV2() - Constructor for class hex.schemas.SplitFrameModelV2.SplitFrameModelOutputV2

SplitFrameV2 - Class in hex.schemas

SplitFrameV2() - Constructor for class hex.schemas.SplitFrameV2

SplitFrameV2.SplitFrameParametersV2 - Class in hex.schemas

SplitFrameV2.SplitFrameParametersV2() - Constructor for class hex.schemas.SplitFrameV2.SplitFrameParametersV2

splits - Variable in class hex.schemas.SplitFrameModelV2.SplitFrameModelOutputV2

standardize - Variable in class hex.schemas.GLMV2.GLMParametersV2

standardize - Variable in class hex.schemas.KMeansV2.KMeansParametersV2

standardize - Variable in class hex.schemas.PCAV2.PCAParametersV2

start_column - Variable in class hex.coxph.CoxPHModel.CoxPHParameters

step(long, Neurons[], DeepLearningModel.DeepLearningModelInfo, boolean, double[]) - Static method in class hex.deeplearning.DeepLearningTask

stop_column - Variable in class hex.coxph.CoxPHModel.CoxPHParameters

subgrad(double, double, double[], double[]) - Static method in class hex.glm.LSMSolver

submodelForLambda(double) - Method in class hex.glm.GLMModel.GLMOutput

submodelIdForLambda(double) - Method in class hex.glm.GLMModel.GLMOutput

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

synonyms - Variable in class hex.schemas.SynonymV1

SynonymsHandler - Class in hex.schemas

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

SynonymV1 - Class in hex.schemas

SynonymV1() - Constructor for class hex.schemas.SynonymV1

T

target - Variable in class hex.schemas.SynonymV1

target_ratio_comm_to_comp - Variable in class hex.schemas.DeepLearningV2.DeepLearningParametersV2

thresholds - Variable in class hex.glm.GLMValidation

ties - Variable in class hex.coxph.CoxPHModel.CoxPHParameters

time_for_communication_us - Variable in class hex.deeplearning.DeepLearningModel

tolerance - Variable in class hex.schemas.PCAV2.PCAParametersV2

toString() - Method in class hex.coxph.CoxPHModel

toString() - Method in class hex.deeplearning.DeepLearningModel.DeepLearningModelInfo

toString() - Method in class hex.deeplearning.DeepLearningModel.Errors

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.FrameTask.DataInfo

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() - 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

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

toStringTree(int, int) - Method in class hex.tree.SharedTreeModel.SharedTreeOutput

train(int, CoxPHV2) - Method in class hex.api.CoxPHBuilderHandler

Required so that Handler.handle() gets the correct schema types.

train(int, DeepLearningV2) - Method in class hex.api.DeepLearningBuilderHandler

Required so that Handler.handle() gets the correct schema types.

train(int, ExampleV2) - Method in class hex.api.ExampleBuilderHandler

Required so that Handler.handle() gets the correct schema types.

train(int, GBMV2) - Method in class hex.api.GBMBuilderHandler

Required so that Handler.handle() gets the correct schema types.

train(int, GLMV2) - Method in class hex.api.GLMBuilderHandler

Required so that Handler.handle() gets the correct schema types.

train(int, GrepV2) - Method in class hex.api.GrepBuilderHandler

Required so that Handler.handle() gets the correct schema types.

train(int, KMeansV2) - Method in class hex.api.KMeansBuilderHandler

Required so that Handler.handle() gets the correct schema types.

train(int, QuantileV2) - Method in class hex.api.QuantileBuilderHandler

Required so that Handler.handle() gets the correct schema types.

train(int, SplitFrameV2) - Method in class hex.api.SplitFrameBuilderHandler

Required so that Handler.handle() gets the correct schema types.

train(int, Word2VecV2) - Method in class hex.api.Word2VecBuilderHandler

Required so that Handler.handle() gets the correct schema types.

train(int, DeepLearningV2) - Method in class hex.schemas.DeepLearningHandler

Deprecated.

train(int, ExampleV2) - Method in class hex.schemas.ExampleHandler

Deprecated.

train(int, GBMV2) - Method in class hex.schemas.GBMHandler

Deprecated.

train(int, GLMV2) - Method in class hex.schemas.GLMHandler

Deprecated.

train(int, GrepV2) - Method in class hex.schemas.GrepHandler

Deprecated.

train(int, KMeansV2) - Method in class hex.schemas.KMeansHandler

Deprecated.

train(int, QuantileV2) - Method in class hex.schemas.QuantileHandler

Deprecated.

train(int, SplitFrameV2) - Method in class hex.schemas.SplitFrameHandler

Deprecated.

train(int, Word2VecV2) - Method in class hex.schemas.Word2VecHandler

Deprecated.

train_confusion_matrix - Variable in class hex.deeplearning.DeepLearningModel.Errors

train_err - Variable in class hex.deeplearning.DeepLearningModel.Errors

train_hitratio - Variable in class hex.deeplearning.DeepLearningModel.Errors

train_mse - Variable in class hex.deeplearning.DeepLearningModel.Errors

train_samples_per_iteration - Variable in class hex.schemas.DeepLearningV2.DeepLearningParametersV2

The number of training data rows to be processed per iteration.

trainAUC - Variable in class hex.deeplearning.DeepLearningModel.Errors

training_rows - Variable in class hex.deeplearning.DeepLearningModel

training_samples - Variable in class hex.deeplearning.DeepLearningModel.Errors

training_time_ms - Variable in class hex.deeplearning.DeepLearningModel.Errors

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.grep.Grep

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

Start the KMeans training Job on an F/J thread.

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

trainModel() - Method in class hex.quantile.Quantile

trainModel() - Method in class hex.splitframe.SplitFrame

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(String) - Method in class hex.word2vec.Word2VecModel

Takes an input string can return the word vector for that word.

treeStats - Variable in class hex.schemas.SharedTreeV2.SharedTreeParametersV2

More indepth tree stats

TreeStats - Class in hex.tree

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

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

tweedie_link_power - Variable in class hex.schemas.GLMV2.GLMParametersV2

tweedie_variance_power - Variable in class hex.schemas.GLMV2.GLMParametersV2

U

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.FrameTask.DataInfo

Undo the standardization/normalization of numerical columns

unstable() - Method in class hex.deeplearning.DeepLearningModel.DeepLearningModelInfo

updateBy(DTree[]) - Method in class hex.tree.TreeStats

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.DeepLearningV2.DeepLearningParametersV2

use_all_factor_levels - Variable in class hex.schemas.GLMV2.GLMParametersV2

user_points - Variable in class hex.schemas.KMeansV2.KMeansParametersV2

V

valid_confusion_matrix - Variable in class hex.deeplearning.DeepLearningModel.Errors

valid_err - Variable in class hex.deeplearning.DeepLearningModel.Errors

valid_hitratio - Variable in class hex.deeplearning.DeepLearningModel.Errors

valid_mse - Variable in class hex.deeplearning.DeepLearningModel.Errors

validate(GLM) - Method in class hex.glm.GLMModel.GLMParameters

validate_parameters(int, CoxPHV2) - Method in class hex.api.CoxPHBuilderHandler

Required so that Handler.handle() gets the correct schema types.

validate_parameters(int, DeepLearningV2) - Method in class hex.api.DeepLearningBuilderHandler

Required so that Handler.handle() gets the correct schema types.

validate_parameters(int, ExampleV2) - Method in class hex.api.ExampleBuilderHandler

Required so that Handler.handle() gets the correct schema types.

validate_parameters(int, GBMV2) - Method in class hex.api.GBMBuilderHandler

Required so that Handler.handle() gets the correct schema types.

validate_parameters(int, GLMV2) - Method in class hex.api.GLMBuilderHandler

Required so that Handler.handle() gets the correct schema types.

validate_parameters(int, GrepV2) - Method in class hex.api.GrepBuilderHandler

Required so that Handler.handle() gets the correct schema types.

validate_parameters(int, KMeansV2) - Method in class hex.api.KMeansBuilderHandler

Required so that Handler.handle() gets the correct schema types.

validate_parameters(int, QuantileV2) - Method in class hex.api.QuantileBuilderHandler

Required so that Handler.handle() gets the correct schema types.

validate_parameters(int, SplitFrameV2) - Method in class hex.api.SplitFrameBuilderHandler

Required so that Handler.handle() gets the correct schema types.

validate_parameters(int, Word2VecV2) - Method in class hex.api.Word2VecBuilderHandler

Required so that Handler.handle() gets the correct schema types.

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

validation_rows - Variable in class hex.deeplearning.DeepLearningModel

validAUC - Variable in class hex.deeplearning.DeepLearningModel.Errors

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.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.FrameTask.DataInfo.TransformType

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.glm.LSMSolver.LSMSolverType

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.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.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.FrameTask.DataInfo.TransformType

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.glm.LSMSolver.LSMSolverType

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.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_importance - Variable in class hex.schemas.GBMV2.GBMParametersV2

variable_importances - Variable in class hex.schemas.DeepLearningV2.DeepLearningParametersV2

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 - Variable in class hex.schemas.SharedTreeV2.SharedTreeParametersV2

Variable Importance, if asked for

vec_nids(Frame, int) - Method in class hex.tree.SharedTree

vec_resp(Frame, int) - Method in class hex.tree.SharedTree

vec_tree(Frame, int) - Method in class hex.tree.SharedTree

vecSize - Variable in class hex.schemas.Word2VecV2.Word2VecParametersV2

visit() - Method in class hex.tree.TreeVisitor

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

W

weights_column - Variable in class hex.coxph.CoxPHModel.CoxPHParameters

windowSize - Variable in class hex.schemas.Word2VecV2.Word2VecParametersV2

withinmse - Variable in class hex.schemas.KMeansModelV2.KMeansModelOutputV2

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

Word2VecHandler - Class in hex.schemas

Deprecated.

Word2VecHandler() - Constructor for class hex.schemas.Word2VecHandler

Deprecated.

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

Word2VecModelV2 - Class in hex.schemas

Word2VecModelV2() - Constructor for class hex.schemas.Word2VecModelV2

Word2VecModelV2.Word2VecModelOutputV2 - Class in hex.schemas

Word2VecModelV2.Word2VecModelOutputV2() - Constructor for class hex.schemas.Word2VecModelV2.Word2VecModelOutputV2

Word2VecV2 - Class in hex.schemas

Word2VecV2() - Constructor for class hex.schemas.Word2VecV2

Word2VecV2.Word2VecParametersV2 - Class in hex.schemas

Word2VecV2.Word2VecParametersV2() - Constructor for class hex.schemas.Word2VecV2.Word2VecParametersV2

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.Word2VecV2.Word2VecParametersV2

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.

_

_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.FrameTask.DataInfo

_adaptedFrame - Variable in class hex.FrameTask.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.

_addedL2 - Variable in class hex.glm.LSMSolver.ADMMSolver

_alpha - Variable in class hex.glm.GLMModel.GLMParameters

_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

_avgbetweenss - Variable in class hex.kmeans.KMeansModel.KMeansOutput

_avgss - Variable in class hex.kmeans.KMeansModel.KMeansOutput

_avgwithinss - Variable in class hex.kmeans.KMeansModel.KMeansOutput

_b - Variable in class hex.deeplearning.Neurons

_bin - Variable in class hex.tree.DTree.Split

_bins - Variable in class hex.tree.DHistogram

_catMissing - Variable in class hex.FrameTask.DataInfo

_catOffsets - Variable in class hex.FrameTask.DataInfo

_catOffsets - Variable in class hex.pca.PCAModel.PCAOutput

_cats - Variable in class hex.FrameTask.DataInfo

_centers - Variable in class hex.kmeans.KMeansModel.KMeansOutput

_centersraw - Variable in class hex.kmeans.KMeansModel.KMeansOutput

_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

_converged - Variable in class hex.glm.LSMSolver

_ct - Variable in class hex.tree.TreeVisitor

_cumVar - Variable in class hex.pca.PCAModel.PCAOutput

_depth - Variable in class hex.tree.DTree

_depth - Variable in class hex.tree.TreeVisitor

_destKeys - Variable in class hex.splitframe.SplitFrameModel.SplitFrameParameters

Destination keys for each output frame split.

_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

_doGrpSplit - Variable in class hex.tree.DHistogram

_dropout - Variable in class hex.deeplearning.Neurons

For Dropout training

_e - Variable in class hex.deeplearning.Neurons

_eigVec - 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

_epsilon - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

The second of two hyper parameters for adaptive learning rate (ADADELTA).

_expert_mode - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

Unlock expert mode parameters than can affect model building speed, predictive accuracy and scoring.

_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.

_foldId - Variable in class hex.FrameTask.DataInfo

_force_load_balance - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

Increase training speed on small datasets by splitting it into many chunks to allow utilization of all cores.

_glm - Variable in class hex.glm.GLMTask

_grad - Variable in class hex.glm.GLMTask.GLMIterationTask

_gradEps - Variable in class hex.optimization.L_BFGS.L_BFGS_Params

_gradient - Variable in class hex.optimization.L_BFGS.GradientInfo

_gradientEps - Variable in class hex.glm.LSMSolver.ADMMSolver

_gram - Variable in class hex.glm.GLMTask.GLMIterationTask

_gram - Variable in class hex.gram.Gram.GramTask

_group_split - Variable in class hex.tree.gbm.GBMModel.GBMParameters

_hasIntercept - 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.

_higher_accuracy - Variable in class hex.glm.GLMModel.GLMParameters

_hs - Variable in class hex.tree.DTree.UndecidedNode

_id - Variable in class hex.glm.LSMSolver

_ignore_const_cols - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

Ignore constant training columns (no information can be gained anyway).

_improved - Variable in class hex.glm.GLMTask.GLMValidationTask

_index - Variable in class hex.deeplearning.Neurons

_init - Variable in class hex.kmeans.KMeansModel.KMeansParameters

_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

_initialPrediction - Variable in class hex.tree.SharedTreeModel.SharedTreeOutput

Initially predicted value (for zero trees)

_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).

_isInt - Variable in class hex.tree.DHistogram

_isWeighted - Variable in class hex.gram.Gram.GramTask

_iters - Variable in class hex.example.ExampleModel.ExampleOutput

_iters - Variable in class hex.kmeans.KMeansModel.KMeansOutput

_iters - Variable in class hex.quantile.QuantileModel.QuantileOutput

_jobKey - Variable in class hex.FrameTask

_jobKey - Variable in class hex.glm.LSMSolver

_k - Variable in class hex.kmeans.KMeansModel.KMeansParameters

_keep_cross_validation_splits - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

_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 - Variable in class hex.glm.GLMTask.GLMValidationTask

_lambda_min_ratio - Variable in class hex.glm.GLMModel.GLMParameters

_lambda_search - Variable in class hex.glm.GLMModel.GLMParameters

_learn_rate - Variable in class hex.tree.gbm.GBMModel.GBMParameters

_leaves - Variable in class hex.tree.DTree

_len - Variable in class hex.tree.DTree

_link - Variable in class hex.glm.GLMModel.GLMParameters

_loss - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

The loss (error) function to be minimized by the model.

_loss - Variable in class hex.tree.gbm.GBMModel.GBMParameters

_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_iters - Variable in class hex.example.ExampleModel.ExampleParameters

_max_iters - Variable in class hex.kmeans.KMeansModel.KMeansParameters

_max_pc - Variable in class hex.pca.PCAModel.PCAParameters

_max_w2 - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

A maximum on the sum of the squared incoming weights into any one neuron.

_maxDepth - Variable in class hex.tree.TreeStats

_maxEx - Variable in class hex.tree.DHistogram

_maxIn - Variable in class hex.tree.DHistogram

_maxIter - Variable in class hex.optimization.L_BFGS.L_BFGS_Params

_maxLeaves - Variable in class hex.tree.TreeStats

_maxs - Variable in class hex.example.ExampleModel.ExampleOutput

_meanDepth - Variable in class hex.tree.TreeStats

_meanLeaves - Variable in class hex.tree.TreeStats

_min - Variable in class hex.tree.DHistogram

_min2 - Variable in class hex.tree.DHistogram

_min_rows - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters

_minDepth - Variable in class hex.tree.TreeStats

_minLeaves - Variable in class hex.tree.TreeStats

_minStep - Variable in class hex.optimization.L_BFGS.L_BFGS_Params

_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.glm.GLMTask.GLMValidationTask

_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.

_mse_train - Variable in class hex.tree.SharedTreeModel.SharedTreeOutput

Train and validation errors per-tree (scored).

_mse_valid - Variable in class hex.tree.SharedTreeModel.SharedTreeOutput

_n_folds - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

_n_folds - Variable in class hex.glm.GLMModel.GLMParameters

_name - Variable in class hex.tree.DHistogram

_namesExp - Variable in class hex.pca.PCAModel.PCAOutput

_nBetas - Variable in class hex.optimization.L_BFGS.L_BFGS_Params

_nbin - Variable in class hex.tree.DHistogram

_nbins - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters

_ncats - Variable in class hex.kmeans.KMeansModel.KMeansOutput

_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.

_nfolds - Variable in class hex.FrameTask.DataInfo

_nid - Variable in class hex.tree.DTree.Node

_nids - Variable in class hex.tree.DTree.DecidedNode

_nlambdas - Variable in class hex.glm.GLMModel.GLMParameters

_nobs - Variable in class hex.gram.Gram.GramTask

_nobs - Variable in class hex.utils.MSETsk

_nodes - Variable in class hex.tree.TreeVisitor

_normModel - Variable in class hex.word2vec.Word2VecModel.Word2VecOutput

_normModel - Variable in class hex.word2vec.Word2VecModel.Word2VecParameters

_normMul - Variable in class hex.FrameTask.DataInfo

_normMul - Variable in class hex.pca.PCAModel.PCAOutput

_normRespMul - Variable in class hex.FrameTask.DataInfo

_normRespSub - Variable in class hex.FrameTask.DataInfo

_normSub - Variable in class hex.FrameTask.DataInfo

_normSub - Variable in class hex.pca.PCAModel.PCAOutput

_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

_numPC - Variable in class hex.pca.PCAModel.PCAOutput

_nums - Variable in class hex.FrameTask.DataInfo

_objVal - Variable in class hex.optimization.L_BFGS.GradientInfo

_offsets - Variable in class hex.grep.GrepModel.GrepOutput

_override_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.

_pid - Variable in class hex.tree.DTree.Node

_pred - Variable in class hex.tree.DTree.LeafNode

_predictor_transform - Variable in class hex.FrameTask.DataInfo

_previous - Variable in class hex.deeplearning.Neurons

References for feed-forward connectivity

_prior - Variable in class hex.glm.GLMModel.GLMParameters

_probs - Variable in class hex.quantile.QuantileModel.QuantileParameters

_propVar - Variable in class hex.pca.PCAModel.PCAOutput

_proximalPenalty - Variable in class hex.glm.LSMSolver.ADMMSolver

_quantiles - Variable in class hex.quantile.QuantileModel.QuantileOutput

_quiet_mode - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

Enable quiet mode for less output to standard output.

_rank - Variable in class hex.pca.PCAModel.PCAOutput

_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.

_ratios - Variable in class hex.splitframe.SplitFrameModel.SplitFrameParameters

Split ratios - resulting number of split is ratios.length+1

_reg - Variable in class hex.glm.GLMTask.GLMIterationTask

_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.

_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)

_res - Variable in class hex.glm.GLMModel.GetScoringModelTask

_res - Variable in class hex.glm.GLMTask.GLMValidationTask

_resDev - Variable in class hex.utils.MSETsk

_response_transform - Variable in class hex.FrameTask.DataInfo

_responses - Variable in class hex.FrameTask.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

_sdev - Variable in class hex.pca.PCAModel.PCAOutput

_seed - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

The random seed controls sampling and initialization.

_seed - Variable in class hex.kmeans.KMeansModel.KMeansParameters

_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.FrameTask

_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

_splits - Variable in class hex.splitframe.SplitFrameModel.SplitFrameOutput

Output frames for each output split part

_standardize - Variable in class hex.glm.GLMModel.GLMParameters

_standardize - Variable in class hex.kmeans.KMeansModel.KMeansParameters

_standardized - Variable in class hex.pca.PCAModel.PCAParameters

_step - Variable in class hex.tree.DHistogram

_stepDec - Variable in class hex.optimization.L_BFGS.L_BFGS_Params

_target_ratio_comm_to_comp - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

_timeLastScoreEnter - Variable in class hex.deeplearning.DeepLearningModel

_tolerance - Variable in class hex.pca.PCAModel.PCAParameters

_train_samples_per_iteration - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

The number of training data rows to be processed per iteration.

_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

_tweedie_link_power - Variable in class hex.glm.GLMModel.GLMParameters

_tweedie_variance_power - Variable in class hex.glm.GLMModel.GLMParameters

_use_all_factor_levels - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

_use_all_factor_levels - Variable in class hex.glm.GLMModel.GLMParameters

_useAllFactorLevels - Variable in class hex.FrameTask.DataInfo

_useFraction - Variable in class hex.FrameTask

_val - Variable in class hex.glm.GLM.GLMGradientInfo

_variable_importance - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters

_variable_importances - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters

Whether to compute variable importances for input features.

_varimp - Variable in class hex.tree.SharedTreeModel.SharedTreeOutput

Variable Importance, if asked for

_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

_wgiven - Variable in class hex.glm.LSMSolver.ADMMSolver

_windowSize - Variable in class hex.word2vec.Word2VecModel.Word2VecOutput

_windowSize - Variable in class hex.word2vec.Word2VecModel.Word2VecParameters

_withinmse - Variable in class hex.kmeans.KMeansModel.KMeansOutput

_wordModel - Variable in class hex.word2vec.Word2VecModel.Word2VecOutput

_wordModel - Variable in class hex.word2vec.Word2VecModel.Word2VecParameters

_xmodels - Variable in class hex.glm.GLMTask.GLMXValidationTask

_xvals - Variable in class hex.glm.GLMTask.GLMXValidationTask

_xx - Variable in class hex.gram.Gram

_xx - Variable in class hex.gram.Gram.Cholesky

_XY - Variable in class hex.gram.Gram.GramTask

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