Index (h2o-algos version 3.12.0.1 API)

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

A

accuracy(int) - Method in class hex.tree.drf.TreeMeasuresCollector.TreeMeasures: Returns a list of accuracies per tree.
accuracy() - Method in class hex.tree.drf.TreeMeasuresCollector.TreeMeasures
accuracy(int) - Method in class hex.tree.drf.TreeMeasuresCollector.TreeSSE
accuracy(int) - Method in class hex.tree.drf.TreeMeasuresCollector.TreeVotes: Returns accuracy per individual trees.
activation - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3: The activation function (non-linearity) to be used by the neurons in the hidden layers.
activation - Variable in class hex.schemas.DeepWaterV3.DeepWaterParametersV3: The activation function (non-linearity) to be used by the neurons in the hidden layers.
activeBC() - Method in class hex.glm.ComputationState
activeCols() - Method in class hex.DataInfo
activeColumns(DHistogram[]) - Static method in class hex.tree.DHistogram
activeData() - Method in class hex.glm.ComputationState
activeDataMultinomial() - Method in class hex.glm.ComputationState
activeDataMultinomial(int) - Method in class hex.glm.ComputationState
actual_best_model_key - Variable in class hex.deeplearning.DeepLearningModel
actual_mtries() - Method in class hex.tree.DTree
actual_train_samples_per_iteration - Variable in class hex.deeplearning.DeepLearningModel
adaptive_rate - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3: The implemented adaptive learning rate algorithm (ADADELTA) automatically combines the benefits of learning rate annealing and momentum training to avoid slow convergence.
add(DeepLearningModelInfo) - Method in class hex.deeplearning.DeepLearningModelInfo: Add another model info into this This will add the weights/biases/learning rate helpers, and the number of processed training samples Note: It will NOT add the elastic averaging helpers, which are always kept constant (they already are the result of a reduction)
add(int, int, float) - Method in class hex.deeplearning.Storage.DenseColMatrix
add(int, int, float) - Method in class hex.deeplearning.Storage.DenseRowMatrix
add(int, double) - Method in class hex.deeplearning.Storage.DenseVector
add(int, int, float) - Method in interface hex.deeplearning.Storage.Matrix
add(int, int, float) - Method in class hex.deeplearning.Storage.SparseRowMatrix
add(int, int, int, float) - Method in interface hex.deeplearning.Storage.Tensor
add(int, double) - Method in interface hex.deeplearning.Storage.Vector
add(DeepWaterModelInfo) - Method in class hex.deepwater.DeepWaterModelInfo
add(double, double[], double, double) - Method in class hex.glm.GLMMetricBuilder
add(double, double, double, double) - Method in class hex.glm.GLMMetricBuilder
add(Gram) - Method in class hex.gram.Gram
add(DHistogram) - Method in class hex.tree.DHistogram
add_processed_global(long) - Method in class hex.deeplearning.DeepLearningModelInfo
add_processed_local(long) - Method in class hex.deeplearning.DeepLearningModelInfo
addDiag(double[]) - Method in class hex.gram.Gram
addDiag(double) - Method in class hex.gram.Gram
addDiag(double, boolean) - Method in class hex.gram.Gram
addExemplar(Aggregator.Exemplar[], Aggregator.Exemplar) - Static method in class hex.aggregator.Aggregator.Exemplar: Add a new exemplar to the input array (doubling it if necessary)
addKTrees(DTree[]) - Method in class hex.tree.SharedTreeModel.SharedTreeOutput
addModelPredictionsToLevelOneFrame(Model, Frame, Frame) - Static method in class hex.ensemble.StackedEnsemble
addNasAtomic(double, double, double) - Method in class hex.tree.DHistogram
addNasPlain(double...) - Method in class hex.tree.DHistogram
addNum(int, double) - Method in class hex.DataInfo.Row
addOutput(String, Vec) - Method in class hex.DataInfo
addResponse(String[], Vec[]) - Method in class hex.DataInfo
addRow(DataInfo.Row, double) - Method in class hex.gram.Gram
addRowDense(DataInfo.Row, double) - Method in class hex.gram.Gram
addRowSparse(DataInfo.Row, double) - Method in class hex.gram.Gram
addSubmodel(GLMModel.Submodel) - Method in class hex.glm.GLMModel
addWAtomic(int, double) - Method in class hex.tree.DHistogram
adjustGradient(double[], double[]) - Method in class hex.glm.GLM.BetaConstraint
ADMM - Class in hex.optimization: Created by tomasnykodym on 3/2/15.
ADMM() - Constructor for class hex.optimization.ADMM
ADMM.L1Solver - Class in hex.optimization
ADMM.L1Solver(double, int, double[]) - Constructor for class hex.optimization.ADMM.L1Solver
ADMM.L1Solver(double, int, double, double, double[]) - Constructor for class hex.optimization.ADMM.L1Solver
ADMM.ProximalSolver - Interface in hex.optimization
aggregate_method - Variable in class hex.schemas.Word2VecTransformV3
Aggregator - Class in hex.aggregator
Aggregator(AggregatorModel.AggregatorParameters) - Constructor for class hex.aggregator.Aggregator
Aggregator(boolean) - Constructor for class hex.aggregator.Aggregator
Aggregator.Exemplar - Class in hex.aggregator
AggregatorModel - Class in hex.aggregator
AggregatorModel(Key, AggregatorModel.AggregatorParameters, AggregatorModel.AggregatorOutput) - Constructor for class hex.aggregator.AggregatorModel
AggregatorModel.AggregatorOutput - Class in hex.aggregator
AggregatorModel.AggregatorOutput(Aggregator) - Constructor for class hex.aggregator.AggregatorModel.AggregatorOutput
AggregatorModel.AggregatorParameters - Class in hex.aggregator
AggregatorModel.AggregatorParameters() - Constructor for class hex.aggregator.AggregatorModel.AggregatorParameters
AggregatorModelV99 - Class in hex.schemas
AggregatorModelV99() - Constructor for class hex.schemas.AggregatorModelV99
AggregatorModelV99.AggregatorModelOutputV99 - Class in hex.schemas
AggregatorModelV99.AggregatorModelOutputV99() - Constructor for class hex.schemas.AggregatorModelV99.AggregatorModelOutputV99
AggregatorV99 - Class in hex.schemas
AggregatorV99() - Constructor for class hex.schemas.AggregatorV99
AggregatorV99.AggregatorParametersV99 - Class in hex.schemas
AggregatorV99.AggregatorParametersV99() - Constructor for class hex.schemas.AggregatorV99.AggregatorParametersV99
algoName() - Method in class hex.aggregator.AggregatorModel.AggregatorParameters
algoName() - Method in class hex.coxph.CoxPHModel.CoxPHParameters
algoName() - Method in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
algoName() - Method in class hex.deepwater.DeepWaterParameters
algoName() - Method in class hex.example.ExampleModel.ExampleParameters
algoName() - Method in class hex.glm.GLMModel.GLMParameters
algoName() - Method in class hex.glrm.GLRMModel.GLRMParameters
algoName() - Method in class hex.grep.GrepModel.GrepParameters
algoName() - Method in class hex.kmeans.KMeansModel.KMeansParameters
algoName() - Method in class hex.naivebayes.NaiveBayesModel.NaiveBayesParameters
algoName() - Method in class hex.pca.PCAModel.PCAParameters
algoName() - Method in class hex.StackedEnsembleModel.StackedEnsembleParameters
algoName() - Method in class hex.svd.SVDModel.SVDParameters
algoName() - Method in class hex.tree.drf.DRFModel.DRFParameters
algoName() - Method in class hex.tree.gbm.GBMModel.GBMParameters
algoName() - Method in class hex.word2vec.Word2VecModel.Word2VecParameters
alpha - Variable in class hex.schemas.GLMV3.GLMParametersV3
append(T) - Method in class hex.tree.drf.TreeMeasuresCollector.TreeMeasures
append(TreeMeasuresCollector.TreeSSE) - Method in class hex.tree.drf.TreeMeasuresCollector.TreeSSE
append(float, double) - Method in class hex.tree.drf.TreeMeasuresCollector.TreeSSE: Append a tree sse to a list of trees.
append(double, double) - Method in class hex.tree.drf.TreeMeasuresCollector.TreeVotes: Append a tree votes to a list of trees.
append(TreeMeasuresCollector.TreeVotes) - Method in class hex.tree.drf.TreeMeasuresCollector.TreeVotes
apply(Env, Env.StackHelp, AstRoot[]) - Method in class water.rapids.prims.word2vec.AstWord2VecToFrame
applyBounds(double, int) - Method in class hex.glm.GLM.BetaConstraint
applyStrongRules(double, double) - Method in class hex.glm.ComputationState: Apply strong rules to filter out expected inactive (with zero coefficient) predictors.
applyStrongRulesMultinomial(double, double) - Method in class hex.glm.ComputationState: Apply strong rules to filter out expected inactive (with zero coefficient) predictors.
applyStrongRulesMultinomial_old(double, double) - Method in class hex.glm.ComputationState: Apply strong rules to filter out expected inactive (with zero coefficient) predictors.
apriori - Variable in class hex.schemas.NaiveBayesModelV3.NaiveBayesModelOutputV3
archetypes - Variable in class hex.schemas.GLRMModelV3.GLRMModelOutputV3
args() - Method in class water.rapids.prims.word2vec.AstWord2VecToFrame
asSSE(TreeMeasuresCollector.TreeMeasures) - Static method in class hex.tree.drf.TreeMeasuresCollector
AstWord2VecToFrame - Class in water.rapids.prims.word2vec: Converts a word2vec model to a Frame
AstWord2VecToFrame() - Constructor for class water.rapids.prims.word2vec.AstWord2VecToFrame
asVotes(TreeMeasuresCollector.TreeMeasures) - Static method in class hex.tree.drf.TreeMeasuresCollector
autoencoder - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
autoencoder - Variable in class hex.schemas.DeepWaterV3.DeepWaterParametersV3
autoEncoderGradient(int, int) - Method in class hex.deeplearning.Neurons: Helper to compute the reconstruction error for auto-encoders (part of the gradient computation)
average_activation - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
avg_change_obj - Variable in class hex.schemas.GLRMModelV3.GLRMModelOutputV3

B

backend - Variable in class hex.schemas.DeepWaterV3.DeepWaterParametersV3
balance_classes - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3: For imbalanced data, balance training data class counts via over/under-sampling.
balance_classes - Variable in class hex.schemas.DeepWaterV3.DeepWaterParametersV3: For imbalanced data, balance training data class counts via over/under-sampling.
balance_classes - Variable in class hex.schemas.GLMV3.GLMParametersV3: For imbalanced data, balance training data class counts via over/under-sampling.
balance_classes - Variable in class hex.schemas.NaiveBayesV3.NaiveBayesParametersV3: For imbalanced data, balance training data class counts via over/under-sampling.
balance_classes - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3: For imbalanced data, balance training data class counts via over/under-sampling.
base_models - Variable in class hex.schemas.StackedEnsembleV99.StackedEnsembleParametersV99
bestCol(DTree.UndecidedNode, DHistogram[]) - Method in class hex.tree.DTree.DecidedNode
bestSubmodel() - Method in class hex.glm.GLMModel.GLMOutput
beta() - Method in class hex.glm.ComputationState
beta() - Method in class hex.glm.GLMModel
beta(double) - Method in class hex.glm.GLMModel
beta() - Method in class hex.glm.GLMModel.GLMOutput
beta - Variable in class hex.glm.GLMModel.Submodel
beta - Variable in class hex.schemas.MakeGLMModelV3
beta_constraints - Variable in class hex.schemas.GLMV3.GLMParametersV3
beta_epsilon - Variable in class hex.schemas.GLMV3.GLMParametersV3
beta_internal() - Method in class hex.glm.GLMModel
beta_std(double) - Method in class hex.glm.GLMModel
betaMultinomial() - Method in class hex.glm.ComputationState
betaMultinomial(int, double[]) - Method in class hex.glm.ComputationState
bin(double) - Method in class hex.tree.DHistogram
bin() - Method in class hex.tree.DTree.Split
binAt(int) - Method in class hex.tree.DHistogram
binIds - Variable in class hex.DataInfo.Row
binomial_double_trees - Variable in class hex.schemas.DRFV3.DRFParametersV3
binomialOpt() - Method in class hex.tree.drf.DRFModel
binomialOpt() - Method in class hex.tree.SharedTreeModel
bins(int) - Method in class hex.tree.DHistogram
bits() - Method in class hex.deeplearning.Dropout
bprop(int) - Method in class hex.deeplearning.Neurons: Back propagation of error terms stored in _e (for non-final layers)
bprop(int) - Method in class hex.deeplearning.Neurons.ExpRectifier
bprop(int) - Method in class hex.deeplearning.Neurons.Input
bprop(int) - Method in class hex.deeplearning.Neurons.Maxout
bprop(int) - Method in class hex.deeplearning.Neurons.Output
bprop(int) - Method in class hex.deeplearning.Neurons.Rectifier
bprop(int) - Method in class hex.deeplearning.Neurons.Tanh
bpropMiniBatch(Neurons[], int) - Static method in class hex.deeplearning.DeepLearningTask: Helper to apply back-propagation without clearing out the gradients afterwards Used for gradient checking
bpropOutputLayer(int) - Method in class hex.deeplearning.Neurons: Back-propagate gradient in output layer
build_tree_one_node - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3
builderVisibility() - Method in class hex.aggregator.Aggregator
builderVisibility() - Method in class hex.coxph.CoxPH
builderVisibility() - Method in class hex.deepwater.DeepWater
builderVisibility() - Method in class hex.ensemble.StackedEnsemble
builderVisibility() - Method in class hex.example.Example
builderVisibility() - Method in class hex.grep.Grep
builderVisibility() - Method in class hex.svd.SVD
builderVisibility() - Method in class hex.word2vec.Word2Vec
buildLayer(Frame, int, int, DTree[], int[], DHistogram[][][], 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
buildNextKTrees() - Method in class hex.tree.SharedTree.Driver
buildTable(String[], boolean) - Method in class hex.glrm.GLRM.Archetypes

C

cache_data - Variable in class hex.schemas.DeepWaterV3.DeepWaterParametersV3
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
calib() - Method in class hex.tree.SharedTree
calib() - Method in class hex.tree.SharedTreeModel.SharedTreeParameters
calibrate_model - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3
calibration_frame - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3
can_build() - Method in class hex.aggregator.Aggregator
can_build() - Method in class hex.coxph.CoxPH
can_build() - Method in class hex.deeplearning.DeepLearning: Types of models we can build with DeepLearning
can_build() - Method in class hex.deepwater.DeepWater: Types of models we can build with DeepWater
can_build() - Method in class hex.ensemble.StackedEnsemble
can_build() - Method in class hex.example.Example
can_build() - Method in class hex.glm.GLM
can_build() - Method in class hex.glrm.GLRM
can_build() - Method in class hex.grep.Grep
can_build() - Method in class hex.kmeans.KMeans
can_build() - Method in class hex.naivebayes.NaiveBayes
can_build() - Method in class hex.pca.PCA
can_build() - Method in class hex.svd.SVD
can_build() - Method in class hex.tree.drf.DRF
can_build() - Method in class hex.tree.gbm.GBM
can_build() - Method in class hex.word2vec.Word2Vec
canonical() - Method in class hex.glm.GLMModel.GLMParameters
catcnt - Variable in class water.api.ModelMetricsGLRMV99
caterr - Variable in class water.api.ModelMetricsGLRMV99
catNAFill() - Method in class hex.DataInfo
catNAFill(int) - Method in class hex.DataInfo
centers - Variable in class hex.schemas.KMeansModelV3.KMeansModelOutputV3
centers_std - Variable in class hex.schemas.KMeansModelV3.KMeansModelOutputV3
channels - Variable in class hex.schemas.DeepWaterV3.DeepWaterParametersV3
check() - Method in class hex.glm.GLM.BetaConstraint
checkAndInheritModelProperties() - Method in class hex.StackedEnsembleModel
checkConsistency() - Method in class hex.aggregator.AggregatorModel
checkKKTs() - Method in class hex.glm.ComputationState
checkKKTsMultinomial() - Method in class hex.glm.ComputationState
checkMemoryFootPrint() - Method in class hex.deeplearning.DeepLearning
checkMemoryFootPrint(DataInfo) - Method in class hex.glm.GLM
checkMemoryFootPrint() - Method in class hex.glrm.GLRM
checkMemoryFootPrint() - Method in class hex.kmeans.KMeans
checkMemoryFootPrint() - Method in class hex.naivebayes.NaiveBayes
checkMemoryFootPrint() - Method in class hex.pca.PCA
checkMemoryFootPrint() - Method in class hex.svd.SVD
checkMemoryFootPrint() - Method in class hex.tree.SharedTree
checksum_impl() - Method in class hex.DataInfo
checksum_impl() - Method in class hex.deeplearning.DeepLearningModel
checksum_impl() - Method in class hex.deeplearning.DeepLearningModelInfo: Unique identifier for this model's state, based on raw numbers
checksum_impl() - Method in class hex.deepwater.DeepWaterModel
checksum_impl() - Method in class hex.glm.GLMModel
checksum_impl() - Method in class hex.glm.GLMModel.GLMOutput
checksum_impl() - Method in class hex.tree.CompressedTree
chk_nids(Chunk[], int) - Method in class hex.tree.SharedTree
chk_offset(Chunk[]) - Method in class hex.tree.SharedTree
chk_oobt(Chunk[]) - Method in class hex.tree.SharedTree
chk_resp(Chunk[]) - Method in class hex.tree.SharedTree
chk_tree(Chunk[], int) - Method in class hex.tree.SharedTree
chk_weight(Chunk[]) - Method in class hex.tree.SharedTree
chk_work(Chunk[], int) - Method in class hex.tree.SharedTree
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: After each chunk, add the number of processed rows to the counter
chunkDone(long) - Method in class hex.FrameTask: Override this to do post-chunk processing work.
chunkDone() - Method in class hex.FrameTask2: Perform action after processing one "chunk" of data/
chunkDone() - Method in class hex.glm.GLMTask.GLMIterationTask
chunkDone() - Method in class hex.gram.Gram.GramTask
chunkDone() - Method in class hex.gram.Gram.OuterGramTask
chunkInit() - Method in class hex.coxph.CoxPH.CoxPHTask
chunkInit() - Method in class hex.deeplearning.DeepLearningTask
chunkInit() - Method in class hex.FrameTask: Override this to initialize at the beginning of chunk processing.
chunkInit() - Method in class hex.FrameTask2: Initialization method, called once per "chunk".
chunkInit() - Method in class hex.glm.GLMTask.ComputeSETsk
chunkInit() - Method in class hex.glm.GLMTask.GLMIterationTask
chunkInit() - Method in class hex.glm.GLMTask.GLMIterationTaskMultinomial
chunkInit() - Method in class hex.glm.GLMTask.GLMMultinomialUpdate
chunkInit() - Method in class hex.glm.GLMTask.GLMMultinomialWLSTask
chunkInit() - Method in class hex.glm.GLMTask.GLMWLSTask
chunkInit() - Method in class hex.glm.GLMTask.LSTask
chunkInit() - Method in class hex.gram.Gram.GramTask
chunkInit() - Method in class hex.gram.Gram.OuterGramTask
cid - Variable in class hex.DataInfo.Row
class_sampling_factors - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3: Desired over/under-sampling ratios per class (lexicographic order).
class_sampling_factors - Variable in class hex.schemas.DeepWaterV3.DeepWaterParametersV3: Desired over/under-sampling ratios per class (lexicographic order).
class_sampling_factors - Variable in class hex.schemas.GLMV3.GLMParametersV3: Desired over/under-sampling ratios per class (lexicographic order).
class_sampling_factors - Variable in class hex.schemas.NaiveBayesV3.NaiveBayesParametersV3: Desired over/under-sampling ratios per class (lexicographic order).
class_sampling_factors - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3: Desired over/under-sampling ratios per class (lexicographic order).
classification_stop - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3: The stopping criteria in terms of classification error (1-accuracy) on the training data scoring dataset.
classification_stop - Variable in class hex.schemas.DeepWaterV3.DeepWaterParametersV3: The stopping criteria in terms of classification error (1-accuracy) on the training data scoring dataset.
classNames() - Method in class hex.glm.GLMModel.GLMOutput
clip_gradient - Variable in class hex.schemas.DeepWaterV3.DeepWaterParametersV3
clone2() - Method in class hex.glm.GLMModel
closeBigScorePredict() - Method in class hex.deepwater.DeepWaterModel
closeLocal() - Method in class hex.deeplearning.DeepLearningTask: After all maps are done on a node, this is called to store the per-node model into DKV (for elastic averaging) Otherwise, do nothing.
closeLocal() - Method in class hex.deepwater.DeepWaterTask: After all maps are done on a node, this is called to store the per-node model into DKV (for elastic averaging) Otherwise, do nothing.
closeLocal() - Method in class hex.FrameTask
ClusteringUtils - Class in hex.util
ClusteringUtils() - Constructor for class hex.util.ClusteringUtils
COD_solve(GLMTask.GLMIterationTask, double, double) - Method in class hex.glm.GLM
coefficient_names - Variable in class hex.schemas.GLMRegularizationPathV3
coefficientNames() - Method in class hex.glm.GLMModel.GLMOutput
coefficients() - Method in class hex.glm.GLMModel: get beta coefficients in a map indexed by name
coefficients - Variable in class hex.schemas.GLMRegularizationPathV3
coefficients_std - Variable in class hex.schemas.GLMRegularizationPathV3
coefNames() - Method in class hex.DataInfo
coefs - Variable in class hex.optimization.L_BFGS.Result
col() - Method in class hex.tree.DTree.Split
col_major - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
col_sample_rate - Variable in class hex.schemas.GBMV3.GBMParametersV3
col_sample_rate_change_per_level - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3
col_sample_rate_per_tree - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3
collectSSE(CompressedTree[], int, Frame, int, float, int, double, SharedTree) - Static method in class hex.tree.drf.TreeMeasuresCollector
collectVotes(CompressedTree[], int, Frame, int, float, int, double, SharedTree) - Static method in class hex.tree.drf.TreeMeasuresCollector
cols() - Method in class hex.deeplearning.Storage.DenseColMatrix
cols() - Method in class hex.deeplearning.Storage.DenseRowMatrix
cols() - Method in interface hex.deeplearning.Storage.Matrix
cols() - Method in class hex.deeplearning.Storage.SparseRowMatrix
cols() - Method in interface hex.deeplearning.Storage.Tensor
compress(int, int, String[][]) - Method in class hex.tree.DTree
compress(AutoBuffer, AutoBuffer) - Method in class hex.tree.DTree.DecidedNode
compress(AutoBuffer, AutoBuffer) - Method in class hex.tree.DTree.LeafNode
compress(AutoBuffer, AutoBuffer) - Method in class hex.tree.DTree.Node
compress(AutoBuffer, AutoBuffer) - Method in class hex.tree.DTree.UndecidedNode
CompressedTree - Class in hex.tree
CompressedTree(byte[], int, long, int, int, String[][]) - Constructor for class hex.tree.CompressedTree
ComputationState - Class in hex.glm
ComputationState(Job, GLMModel.GLMParameters, DataInfo, GLM.BetaConstraint, int) - Constructor for class hex.glm.ComputationState
ComputationState.GLMSubsetGinfo - Class in hex.glm
ComputationState.GLMSubsetGinfo(GLM.GLMGradientInfo, int, int, int[]) - Constructor for class hex.glm.ComputationState.GLMSubsetGinfo
compute_metrics - Variable in class hex.schemas.NaiveBayesV3.NaiveBayesParametersV3
compute_metrics - Variable in class hex.schemas.PCAV3.PCAParametersV3
compute_p_values - Variable in class hex.schemas.GLMV3.GLMParametersV3
computeAIC() - Method in class hex.glm.GLMMetricBuilder
computeCrossValidation() - Method in class hex.glm.GLM: GLM implementation of N-fold cross-validation.
computeGram(int, GramV3) - Method in class hex.api.MakeGLMModelHandler
computeImpl() - Method in class hex.coxph.CoxPH.CoxPHDriver
computeImpl() - Method in class hex.deeplearning.DeepLearning.DeepLearningDriver
computeImpl() - Method in class hex.deepwater.DeepWater.DeepWaterDriver
computeImpl() - Method in class hex.glm.GLM.GLMDriver
computeImpl() - Method in class hex.tree.SharedTree.Driver
computePriorClassDistribution() - Method in class hex.glm.GLM
computePriorClassDistribution() - Method in class hex.tree.SharedTree
computeQ(Key<Job>, DataInfo, Frame, double[][]) - Static method in class hex.util.LinearAlgebraUtils: Solve for Q from Y = QR factorization and write into new frame
computeQInPlace(Key<Job>, DataInfo) - Static method in class hex.util.LinearAlgebraUtils: Solve for Q from Y = QR factorization and write into Y frame
computeR(Key<Job>, DataInfo, boolean, double[][]) - Static method in class hex.util.LinearAlgebraUtils: Get R = L' from Cholesky decomposition Y'Y = LL' (same as R from Y = QR)
computeStats() - Method in class hex.deeplearning.DeepLearningModelInfo: Compute statistics about this model on all nodes
computeSubmodel(int, double) - Method in class hex.glm.GLM.GLMDriver
computeVariableImportances() - Method in class hex.deeplearning.DeepLearningModelInfo: Compute Variable Importance, based on GEDEON: DATA MINING OF INPUTS: ANALYSING MAGNITUDE AND FUNCTIONAL MEASURES
computeWeights(double, double, double, double, GLMModel.GLMWeights) - Method in class hex.glm.GLMModel.GLMWeightsFun
converged() - Method in class hex.glm.ComputationState
converged - Variable in class hex.optimization.L_BFGS.Result
count - Variable in class hex.schemas.Word2VecSynonymsV3
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
CoxPHModel - Class in hex.coxph: The Deep Learning model It contains a DeepLearningModelInfo with the most up-to-date model, a scoring history, as well as some helpers to indicate the progress
CoxPHModel(Key, CoxPHModel.CoxPHParameters, CoxPHModel.CoxPHOutput) - Constructor for class hex.coxph.CoxPHModel
CoxPHModel.CoxPHOutput - Class in hex.coxph
CoxPHModel.CoxPHOutput(CoxPH) - Constructor for class hex.coxph.CoxPHModel.CoxPHOutput
CoxPHModel.CoxPHParameters - Class in hex.coxph
CoxPHModel.CoxPHParameters() - Constructor for class hex.coxph.CoxPHModel.CoxPHParameters
CoxPHModel.CoxPHParameters.CoxPHTies - Enum in hex.coxph
CoxPHModelV3 - Class in hex.schemas
CoxPHModelV3() - Constructor for class hex.schemas.CoxPHModelV3
CoxPHModelV3.CoxPHModelOutputV3 - Class in hex.schemas
CoxPHModelV3.CoxPHModelOutputV3() - Constructor for class hex.schemas.CoxPHModelV3.CoxPHModelOutputV3
CoxPHV3 - Class in hex.schemas
CoxPHV3() - Constructor for class hex.schemas.CoxPHV3
CoxPHV3.CoxPHParametersV3 - Class in hex.schemas
CoxPHV3.CoxPHParametersV3() - Constructor for class hex.schemas.CoxPHV3.CoxPHParametersV3
createCenterTable(ClusteringModel.ClusteringOutput, boolean) - Static method in class hex.util.ClusteringUtils
createFrameOfExemplars(Frame, Key) - Method in class hex.aggregator.AggregatorModel
createImpl() - Method in class hex.schemas.AggregatorModelV99
createImpl() - Method in class hex.schemas.CoxPHModelV3
createImpl() - Method in class hex.schemas.CoxPHV3.CoxPHParametersV3
createImpl() - Method in class hex.schemas.DeepLearningModelV3
createImpl() - Method in class hex.schemas.DeepWaterModelV3
createImpl() - Method in class hex.schemas.DRFModelV3
createImpl() - Method in class hex.schemas.GBMModelV3
createImpl() - Method in class hex.schemas.GLMModelV3
createImpl() - Method in class hex.schemas.GLRMModelV3
createImpl() - Method in class hex.schemas.GrepModelV3
createImpl() - Method in class hex.schemas.GrepModelV3.GrepModelOutputV3
createImpl() - Method in class hex.schemas.KMeansModelV3
createImpl() - Method in class hex.schemas.NaiveBayesModelV3
createImpl() - Method in class hex.schemas.PCAModelV3
createImpl() - Method in class hex.schemas.StackedEnsembleModelV99
createImpl() - Method in class hex.schemas.SVDModelV99
createImpl() - Method in class hex.schemas.Word2VecModelV3
createInitialModelInfo(Word2VecModel.Word2VecParameters) - Static method in class hex.word2vec.Word2VecModel.Word2VecModelInfo
createModelSummaryTable(int, TreeStats) - Static method in class hex.tree.SharedTree
createOutputSchema() - Method in class hex.schemas.AggregatorModelV99
createOutputSchema() - Method in class hex.schemas.CoxPHModelV3
createOutputSchema() - Method in class hex.schemas.DeepLearningModelV3
createOutputSchema() - Method in class hex.schemas.DeepWaterModelV3
createOutputSchema() - Method in class hex.schemas.DRFModelV3
createOutputSchema() - Method in class hex.schemas.ExampleModelV3
createOutputSchema() - Method in class hex.schemas.GBMModelV3
createOutputSchema() - Method in class hex.schemas.GLMModelV3
createOutputSchema() - Method in class hex.schemas.GLRMModelV3
createOutputSchema() - Method in class hex.schemas.GrepModelV3
createOutputSchema() - Method in class hex.schemas.KMeansModelV3
createOutputSchema() - Method in class hex.schemas.NaiveBayesModelV3
createOutputSchema() - Method in class hex.schemas.PCAModelV3
createOutputSchema() - Method in class hex.schemas.StackedEnsembleModelV99
createOutputSchema() - Method in class hex.schemas.SVDModelV99
createOutputSchema() - Method in class hex.schemas.Word2VecModelV3
createParametersSchema() - Method in class hex.schemas.AggregatorModelV99
createParametersSchema() - Method in class hex.schemas.CoxPHModelV3
createParametersSchema() - Method in class hex.schemas.DeepLearningModelV3
createParametersSchema() - Method in class hex.schemas.DeepWaterModelV3
createParametersSchema() - Method in class hex.schemas.DRFModelV3
createParametersSchema() - Method in class hex.schemas.ExampleModelV3
createParametersSchema() - Method in class hex.schemas.GBMModelV3
createParametersSchema() - Method in class hex.schemas.GLMModelV3
createParametersSchema() - Method in class hex.schemas.GLRMModelV3
createParametersSchema() - Method in class hex.schemas.GrepModelV3
createParametersSchema() - Method in class hex.schemas.KMeansModelV3
createParametersSchema() - Method in class hex.schemas.NaiveBayesModelV3
createParametersSchema() - Method in class hex.schemas.PCAModelV3
createParametersSchema() - Method in class hex.schemas.StackedEnsembleModelV99
createParametersSchema() - Method in class hex.schemas.SVDModelV99
createParametersSchema() - Method in class hex.schemas.Word2VecModelV3
createScoringHistoryTable(Model.Output, ScoreKeeper[], ScoreKeeper[], Job, long[]) - Static method in class hex.tree.SharedTree
createScoringHistoryTableDR(LinkedHashMap<String, ArrayList>, String, long) - Static method in class hex.util.DimensionReductionUtils: Create the scoring history for dimension reduction algorithms like PCA/SVD.
ctree(int, int) - Method in class hex.tree.SharedTreeModel.SharedTreeOutput
cv_computeAndSetOptimalParameters(ModelBuilder[]) - Method in class hex.deeplearning.DeepLearning
cv_computeAndSetOptimalParameters(ModelBuilder<DeepWaterModel, DeepWaterParameters, DeepWaterModelOutput>[]) - Method in class hex.deepwater.DeepWater
cv_computeAndSetOptimalParameters(ModelBuilder[]) - Method in class hex.glm.GLM: If run with lambda search, we need to take extra action performed after cross-val models are built.
cv_computeAndSetOptimalParameters(ModelBuilder<M, P, O>[]) - Method in class hex.tree.SharedTree

D

d - Variable in class hex.schemas.SVDModelV99.SVDModelOutputV99
data(Chunk[], int, int) - Method in class hex.kmeans.KMeansModel
data_info - Variable in class hex.deeplearning.DeepLearningModelInfo
data_info() - Method in class hex.deeplearning.DeepLearningModelInfo
data_row(Chunk[], int, double[]) - Method in class hex.tree.SharedTree
DataInfo - Class in hex: Created by tomasnykodym on 1/29/15.
DataInfo(Frame, Frame, boolean, DataInfo.TransformType, boolean, boolean, boolean) - Constructor for class hex.DataInfo
DataInfo(Frame, Frame, int, boolean, DataInfo.TransformType, DataInfo.TransformType, boolean, boolean, boolean, boolean, boolean, boolean) - Constructor for class hex.DataInfo
DataInfo(Frame, Frame, int, boolean, DataInfo.TransformType, DataInfo.TransformType, boolean, boolean, boolean, boolean, boolean, boolean, String[]) - Constructor for class hex.DataInfo: The train/valid Frame instances are sorted by categorical (themselves sorted by cardinality greatest to least) with all numerical columns following.
DataInfo(Frame, Frame, int, boolean, DataInfo.TransformType, DataInfo.TransformType, boolean, boolean, boolean, boolean, boolean, boolean, boolean) - Constructor for class hex.DataInfo
DataInfo.Row - Class in hex
DataInfo.Row(boolean, int, int, int, int, long) - Constructor for class hex.DataInfo.Row
DataInfo.Row(boolean, double[], int[], double[], int, long) - Constructor for class hex.DataInfo.Row
DataInfo.Row(double[]) - Constructor for class hex.DataInfo.Row
DataInfo.Rows - Class in hex
DataInfo.TransformType - Enum in hex
DataInfoFrameV3 - Class in hex.schemas
DataInfoFrameV3() - Constructor for class hex.schemas.DataInfoFrameV3
decided(int) - Method in class hex.tree.DTree
DECIDED_ROW - Static variable in class hex.tree.ScoreBuildHistogram: Marker for already decided row.
decompose_2(double[][], int, int) - Static method in class hex.gram.Gram.InPlaceCholesky
deep_clone() - Method in class hex.gram.Gram
deepClone(Key<M>) - Method in class hex.tree.SharedTreeModel: Performs deep clone of given model.
DeepLearning - Class in hex.deeplearning: Deep Learning Neural Net implementation based on MRTask
DeepLearning(DeepLearningModel.DeepLearningParameters) - Constructor for class hex.deeplearning.DeepLearning: Main constructor from Deep Learning parameters
DeepLearning(DeepLearningModel.DeepLearningParameters, Key<DeepLearningModel>) - Constructor for class hex.deeplearning.DeepLearning
DeepLearning(boolean) - Constructor for class hex.deeplearning.DeepLearning
DeepLearning.DeepLearningDriver - Class in hex.deeplearning
DeepLearning.DeepLearningDriver() - Constructor for class hex.deeplearning.DeepLearning.DeepLearningDriver
DeepLearningModel - Class in hex.deeplearning: The Deep Learning model It contains a DeepLearningModelInfo with the most up-to-date model, a scoring history, as well as some helpers to indicate the progress
DeepLearningModel(Key, DeepLearningModel.DeepLearningParameters, DeepLearningModel, boolean, DataInfo) - Constructor for class hex.deeplearning.DeepLearningModel: Constructor to restart from a checkpointed model
DeepLearningModel(Key, DeepLearningModel.DeepLearningParameters, DeepLearningModel.DeepLearningModelOutput, Frame, Frame, int) - Constructor for class hex.deeplearning.DeepLearningModel: Regular constructor (from scratch)
DeepLearningModel.DeepLearningModelOutput - Class in hex.deeplearning: The Deep Learning model output contains a few extra fields in addition to the metrics in Model.Output 1) Scoring history (raw data) 2) weights/biases (raw data) 3) variable importances (TwoDimTable)
DeepLearningModel.DeepLearningModelOutput(DeepLearning) - Constructor for class hex.deeplearning.DeepLearningModel.DeepLearningModelOutput
DeepLearningModel.DeepLearningParameters - Class in hex.deeplearning: Deep Learning Parameters
DeepLearningModel.DeepLearningParameters() - Constructor for class hex.deeplearning.DeepLearningModel.DeepLearningParameters
DeepLearningModel.DeepLearningParameters.Activation - Enum in hex.deeplearning: Activation functions
DeepLearningModel.DeepLearningParameters.ClassSamplingMethod - Enum in hex.deeplearning
DeepLearningModel.DeepLearningParameters.InitialWeightDistribution - Enum in hex.deeplearning
DeepLearningModel.DeepLearningParameters.Loss - Enum in hex.deeplearning: Loss functions Absolute, Quadratic, Huber, Quantile for regression Quadratic, ModifiedHuber or CrossEntropy for classification
DeepLearningModel.DeepLearningParameters.MissingValuesHandling - Enum in hex.deeplearning
DeepLearningModelInfo - Class in hex.deeplearning: This class contains the state of the Deep Learning model This will be shared: one per node
DeepLearningModelInfo(DeepLearningModel.DeepLearningParameters, Key, DataInfo, int, Frame, Frame) - Constructor for class hex.deeplearning.DeepLearningModelInfo: Main constructor
DeepLearningModelInfo.GradientCheck - Class in hex.deeplearning
DeepLearningModelV3 - Class in hex.schemas
DeepLearningModelV3() - Constructor for class hex.schemas.DeepLearningModelV3
DeepLearningModelV3.DeepLearningModelOutputV3 - Class in hex.schemas
DeepLearningModelV3.DeepLearningModelOutputV3() - Constructor for class hex.schemas.DeepLearningModelV3.DeepLearningModelOutputV3
DeepLearningScoringInfo - Class in hex.deeplearning: Lightweight DeepLearning scoring history.
DeepLearningScoringInfo() - Constructor for class hex.deeplearning.DeepLearningScoringInfo
DeepLearningTask - Class in hex.deeplearning
DeepLearningTask(Key, DeepLearningModelInfo, float, int) - Constructor for class hex.deeplearning.DeepLearningTask: The only constructor
DeepLearningTask(Key, DeepLearningModelInfo, float, int, H2O.H2OCountedCompleter) - Constructor for class hex.deeplearning.DeepLearningTask
DeepLearningTask2 - Class in hex.deeplearning: DRemoteTask-based Deep Learning.
DeepLearningTask2(Key, Frame, DeepLearningModelInfo, float, int) - Constructor for class hex.deeplearning.DeepLearningTask2: Construct a DeepLearningTask2 where every node trains on the entire training dataset
DeepLearningV3 - Class in hex.schemas
DeepLearningV3() - Constructor for class hex.schemas.DeepLearningV3
DeepLearningV3.DeepLearningParametersV3 - Class in hex.schemas
DeepLearningV3.DeepLearningParametersV3() - Constructor for class hex.schemas.DeepLearningV3.DeepLearningParametersV3
DeepWater - Class in hex.deepwater: Deep Learning Neural Net implementation based on MRTask
DeepWater(DeepWaterParameters) - Constructor for class hex.deepwater.DeepWater: Main constructor from Deep Learning parameters
DeepWater(boolean) - Constructor for class hex.deepwater.DeepWater
DeepWater.DeepWaterDriver - Class in hex.deepwater
DeepWater.DeepWaterDriver() - Constructor for class hex.deepwater.DeepWater.DeepWaterDriver
DeepWaterModel - Class in hex.deepwater: The Deep Learning model It contains a DeepWaterModelInfo with the most up-to-date model, a scoring history, as well as some helpers to indicate the progress
DeepWaterModel(Key<DeepWaterModel>, DeepWaterParameters, DeepWaterModel, DataInfo) - Constructor for class hex.deepwater.DeepWaterModel: Constructor to restart from a checkpointed model
DeepWaterModel(Key<DeepWaterModel>, DeepWaterParameters, DeepWaterModelOutput, Frame, Frame, int) - Constructor for class hex.deepwater.DeepWaterModel: Regular constructor (from scratch)
DeepWaterModelInfo - Class in hex.deepwater: This class contains the state of the Deep Learning model This will be shared: one per node
DeepWaterModelOutput - Class in hex.deepwater
DeepWaterModelOutput(DeepWater) - Constructor for class hex.deepwater.DeepWaterModelOutput: The Deep Learning model output contains a few extra fields in addition to the metrics in Model.Output 1) Scoring history (raw data) 2) weights/biases (raw data) 3) variable importances (TwoDimTable)
DeepWaterModelV3 - Class in hex.schemas
DeepWaterModelV3() - Constructor for class hex.schemas.DeepWaterModelV3
DeepWaterModelV3.DeepWaterModelOutputV3 - Class in hex.schemas
DeepWaterModelV3.DeepWaterModelOutputV3() - Constructor for class hex.schemas.DeepWaterModelV3.DeepWaterModelOutputV3
DeepwaterMojoWriter - Class in hex.deepwater: Mojo definition for DeepWater model.
DeepwaterMojoWriter() - Constructor for class hex.deepwater.DeepwaterMojoWriter
DeepwaterMojoWriter(DeepWaterModel) - Constructor for class hex.deepwater.DeepwaterMojoWriter
DeepWaterParameters - Class in hex.deepwater: Parameters for a Deep Water image classification model
DeepWaterParameters() - Constructor for class hex.deepwater.DeepWaterParameters
DeepWaterParameters.Activation - Enum in hex.deepwater: Activation functions
DeepWaterParameters.Backend - Enum in hex.deepwater
DeepWaterParameters.MissingValuesHandling - Enum in hex.deepwater
DeepWaterParameters.Network - Enum in hex.deepwater
DeepWaterParameters.ProblemType - Enum in hex.deepwater
DeepWaterScoringInfo - Class in hex.deepwater: Lightweight DeepLearning scoring history.
DeepWaterScoringInfo() - Constructor for class hex.deepwater.DeepWaterScoringInfo
DeepWaterTask - Class in hex.deepwater
DeepWaterV3 - Class in hex.schemas
DeepWaterV3() - Constructor for class hex.schemas.DeepWaterV3
DeepWaterV3.DeepWaterParametersV3 - Class in hex.schemas
DeepWaterV3.DeepWaterParametersV3() - Constructor for class hex.schemas.DeepWaterV3.DeepWaterParametersV3
DEFAULT_ABSTOL - Static variable in class hex.optimization.ADMM.L1Solver
DEFAULT_RELTOL - Static variable in class hex.optimization.ADMM.L1Solver
defaultLink - Variable in enum hex.glm.GLMModel.GLMParameters.Family
defaultStoppingTolerance() - Method in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
defaultStoppingTolerance() - Method in class hex.deepwater.DeepWaterParameters
delete() - Method in class hex.deeplearning.DeepLearningModel
delete() - Method in class hex.word2vec.Word2VecModel
denormalizeBeta(double[]) - Method in class hex.DataInfo
desiredChunks(Frame, boolean) - Method in class hex.deeplearning.DeepLearning
dest - Variable in class hex.schemas.MakeGLMModelV3
destination_frame - Variable in class hex.schemas.GramV3
dev - Variable in class hex.glm.GLMModel.GLMWeights
DEV_DEBUG - Static variable in class hex.tree.SharedTree
deviance() - Method in class hex.glm.ComputationState
deviance(double, double, double) - Method in class hex.glm.GLMModel
deviance(double, double) - Method in class hex.glm.GLMModel.GLMParameters
deviance(float, float) - Method in class hex.glm.GLMModel.GLMParameters
deviance(double, double) - Method in class hex.glm.GLMModel.GLMWeightsFun
deviance(float, float) - Method in class hex.glm.GLMModel.GLMWeightsFun
devianceTest - Variable in class hex.glm.GLMModel.Submodel
devianceTrain - Variable in class hex.glm.GLMModel.Submodel
device_id - Variable in class hex.schemas.DeepWaterV3.DeepWaterParametersV3
dfork2(byte[], Frame, boolean) - Method in class hex.tree.ScoreBuildHistogram
dfork2(byte[], Frame, boolean) - Method in class hex.tree.ScoreBuildHistogram2
DHistogram - Class in hex.tree: A Histogram, computed in parallel over a Vec.
DHistogram(String, int, int, byte, double, double, double, SharedTreeModel.SharedTreeParameters.HistogramType, long, Key) - Constructor for class hex.tree.DHistogram
DHistogram.NASplitDir - Enum in hex.tree: Split direction for missing values.
DhnasdLeft - Static variable in class hex.tree.TreeVisitor
DhnasdNaLeft - Static variable in class hex.tree.TreeVisitor
DhnasdNaVsRest - Static variable in class hex.tree.TreeVisitor
diagnostics - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3: Gather diagnostics for hidden layers, such as mean and RMS values of learning rate, momentum, weights and biases.
diagnostics - Variable in class hex.schemas.DeepWaterV3.DeepWaterParametersV3: Gather diagnostics for hidden layers, such as mean and RMS values of learning rate, momentum, weights and biases.
diagSum() - Method in class hex.gram.Gram
DimensionReductionUtils - Class in hex.util: Created by wendycwong on 2/9/17.
DimensionReductionUtils() - Constructor for class hex.util.DimensionReductionUtils
dinfo() - Method in class hex.FrameTask
dinfo() - Method in class hex.glm.GLMModel
div(double) - Method in class hex.deeplearning.DeepLearningModelInfo: Divide all weights/biases by a real-valued number
div(double) - Method in class hex.deepwater.DeepWaterModelInfo
do_not_split() - Method in class hex.tree.DTree.UndecidedNode
doOOBScoring() - Method in class hex.tree.SharedTree.Driver
doScoreMetrics(Job) - Method in class hex.StackedEnsembleModel
doScoreMetricsOneFrame(Frame, Job) - Method in class hex.StackedEnsembleModel
doScoringAndSaveModel(boolean, boolean, boolean) - Method in class hex.tree.SharedTree
dotSame(DataInfo.Row) - Method in class hex.DataInfo.Row
DRF - Class in hex.tree.drf: Gradient Boosted Trees Based on "Elements of Statistical Learning, Second Edition, page 387"
DRF(DRFModel.DRFParameters) - Constructor for class hex.tree.drf.DRF
DRF(DRFModel.DRFParameters, Key<DRFModel>) - Constructor for class hex.tree.drf.DRF
DRF(DRFModel.DRFParameters, Job) - Constructor for class hex.tree.drf.DRF
DRF(boolean) - Constructor for class hex.tree.drf.DRF
DRFModel - Class in hex.tree.drf
DRFModel(Key<DRFModel>, DRFModel.DRFParameters, DRFModel.DRFOutput) - Constructor for class hex.tree.drf.DRFModel
DRFModel.DRFOutput - Class in hex.tree.drf
DRFModel.DRFOutput(DRF) - Constructor for class hex.tree.drf.DRFModel.DRFOutput
DRFModel.DRFParameters - Class in hex.tree.drf
DRFModel.DRFParameters() - Constructor for class hex.tree.drf.DRFModel.DRFParameters
DRFModelV3 - Class in hex.schemas
DRFModelV3() - Constructor for class hex.schemas.DRFModelV3
DRFModelV3.DRFModelOutputV3 - Class in hex.schemas
DRFModelV3.DRFModelOutputV3() - Constructor for class hex.schemas.DRFModelV3.DRFModelOutputV3
DrfMojoWriter - Class in hex.tree.drf: Mojo definition for DRF model.
DrfMojoWriter() - Constructor for class hex.tree.drf.DrfMojoWriter
DrfMojoWriter(DRFModel) - Constructor for class hex.tree.drf.DrfMojoWriter
DRFV3 - Class in hex.schemas
DRFV3() - Constructor for class hex.schemas.DRFV3
DRFV3.DRFParametersV3 - Class in hex.schemas
DRFV3.DRFParametersV3() - Constructor for class hex.schemas.DRFV3.DRFParametersV3
dropActiveData() - Method in class hex.glm.ComputationState
dropCols(int[]) - Method in class hex.gram.Gram
dropInteractions() - Method in class hex.DataInfo
dropIntercept() - Method in class hex.gram.Gram
Dropout - Class in hex.deeplearning: Helper class for dropout training of Neural Nets
dropWeights() - Method in class hex.DataInfo
DTree - Class in hex.tree: A Decision Tree, laid over a Frame of Vecs, and built distributed.
DTree(Frame, int, char, int, int, long, SharedTreeModel.SharedTreeParameters) - 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, DHistogram.NASplitDir, IcedBitSet, byte, double, double, double, double, double, 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, SharedTree, Key[][]) - Constructor for class hex.tree.DTreeScorer

E

early_stopping - Variable in class hex.schemas.GLMV3.GLMParametersV3
eigenvectors - Variable in class hex.schemas.GLRMModelV3.GLRMModelOutputV3
eigenvectors - Variable in class hex.schemas.PCAModelV3.PCAModelOutputV3
elastic_averaging - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
elastic_averaging_moving_rate - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
elastic_averaging_regularization - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
elasticAverageModelInfoKey() - Method in class hex.deeplearning.DeepLearningModelInfo
epoch_counter - Variable in class hex.deeplearning.DeepLearningModel
epoch_counter - Variable in class hex.deeplearning.DeepLearningScoringInfo
epoch_counter() - Method in class hex.deeplearning.DeepLearningScoringInfo
epoch_counter() - Method in class hex.deepwater.DeepWaterScoringInfo
epochs - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3: The number of passes over the training dataset to be carried out.
epochs - Variable in class hex.schemas.DeepWaterV3.DeepWaterParametersV3: The number of passes over the training dataset to be carried out.
epochs - Variable in class hex.schemas.Word2VecV3.Word2VecParametersV3
eps_prob - Variable in class hex.schemas.NaiveBayesV3.NaiveBayesParametersV3
eps_sdev - Variable in class hex.schemas.NaiveBayesV3.NaiveBayesParametersV3
epsilon - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3: The second of two hyper parameters for adaptive learning rate (ADADELTA).
estimate_k - Variable in class hex.schemas.KMeansV3.KMeansParametersV3
estimateRho(double, double, double, double) - Static method in class hex.optimization.ADMM.L1Solver: Estimate optimal rho based on l1 penalty and (estimate of) solution x without the l1penalty
evaluate(double[]) - Method in interface hex.optimization.OptimizationUtils.LineSearchSolver
evaluate(double[]) - Method in class hex.optimization.OptimizationUtils.MoreThuente
evaluate(double[]) - Method in class hex.optimization.OptimizationUtils.SimpleBacktrackingLS
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
ExampleModel - Class in hex.example
ExampleModel.ExampleOutput - Class in hex.example
ExampleModel.ExampleOutput(Example) - Constructor for class hex.example.ExampleModel.ExampleOutput
ExampleModel.ExampleParameters - Class in hex.example
ExampleModel.ExampleParameters() - Constructor for class hex.example.ExampleModel.ExampleParameters
ExampleModelV3 - Class in hex.schemas
ExampleModelV3() - Constructor for class hex.schemas.ExampleModelV3
ExampleModelV3.ExampleModelOutputV3 - Class in hex.schemas
ExampleModelV3.ExampleModelOutputV3() - Constructor for class hex.schemas.ExampleModelV3.ExampleModelOutputV3
ExampleV3 - Class in hex.schemas
ExampleV3() - Constructor for class hex.schemas.ExampleV3
ExampleV3.ExampleParametersV3 - Class in hex.schemas
ExampleV3.ExampleParametersV3() - Constructor for class hex.schemas.ExampleV3.ExampleParametersV3
expand(Frame, String[], boolean, boolean, boolean) - Static method in class hex.glm.GLMModel.GLMOutput
expand_user_y - Variable in class hex.schemas.GLRMV3.GLRMParametersV3
expandBeta(double[]) - Method in class hex.glm.ComputationState
expandCats() - Method in class hex.DataInfo.Row
expandCats(double[][], DataInfo) - Static method in class hex.glrm.GLRM
expandRow(double[], DataInfo, double[], boolean) - Static method in class hex.util.LinearAlgebraUtils
explained_deviance_train - Variable in class hex.schemas.GLMRegularizationPathV3
explained_deviance_valid - Variable in class hex.schemas.GLMRegularizationPathV3
explainedDev() - Method in class hex.glm.GLMMetricBuilder
export_native_parameters_prefix - Variable in class hex.schemas.DeepWaterV3.DeepWaterParametersV3
export_weights_and_biases - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
extractDenseRow(Chunk[], int, DataInfo.Row) - Method in class hex.DataInfo
extractRegularizationPath(int, GLMRegularizationPathV3) - Method in class hex.api.MakeGLMModelHandler
extractSparseRows(Chunk[]) - Method in class hex.DataInfo: Extract (sparse) rows from given chunks.

F

family - Variable in class hex.schemas.GLMV3.GLMParametersV3
fast_mode - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3: Enable fast mode (minor approximation in back-propagation), should not affect results significantly.
fields - Static variable in class hex.schemas.AggregatorV99.AggregatorParametersV99
fields - Static variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
fields - Static variable in class hex.schemas.DeepWaterV3.DeepWaterParametersV3
fields - Static variable in class hex.schemas.DRFV3.DRFParametersV3
fields - Static variable in class hex.schemas.GBMV3.GBMParametersV3
fields - Static variable in class hex.schemas.GLMV3.GLMParametersV3
fields - Static variable in class hex.schemas.GLRMV3.GLRMParametersV3
fields - Static variable in class hex.schemas.KMeansV3.KMeansParametersV3
fields - Static variable in class hex.schemas.NaiveBayesV3.NaiveBayesParametersV3
fields - Static variable in class hex.schemas.PCAV3.PCAParametersV3
fields - Static variable in class hex.schemas.StackedEnsembleV99.StackedEnsembleParametersV99
fields - Static variable in class hex.schemas.SVDV99.SVDParametersV99
fields - Static variable in class hex.schemas.Word2VecV3.Word2VecParametersV3
fillBytes(long) - Method in class hex.deeplearning.Dropout
fillFromImpl(GLMModel.GLMOutput) - Method in class hex.schemas.GLMModelV3.GLMModelOutputV3
fillFromImpl(GrepModel) - Method in class hex.schemas.GrepModelV3
fillFromImpl(GrepModel.GrepOutput) - Method in class hex.schemas.GrepModelV3.GrepModelOutputV3
fillFromImpl(KMeansModel.KMeansOutput) - Method in class hex.schemas.KMeansModelV3.KMeansModelOutputV3
filterExpandedColumns(int[]) - Method in class hex.DataInfo: Filter the _adaptedFrame so that it contains only the Vecs referenced by the cols parameter.
filterExpandedColumns(int[]) - Method in class hex.glm.GLM.BetaConstraint
find_maxEx() - Method in class hex.tree.DHistogram
find_maxEx(double, int) - Static method in class hex.tree.DHistogram
find_maxIn() - Method in class hex.tree.DHistogram
find_min() - Method in class hex.tree.DHistogram
findSynonyms(int, Word2VecSynonymsV3) - Method in class hex.api.Word2VecHandler
findSynonyms(String, int) - Method in class hex.word2vec.Word2VecModel: Find synonyms (i.e.
findZeroCols() - Method in class hex.gram.Gram
fold_assignment - Variable in class hex.StackedEnsembleModel
fold_column - Variable in class hex.StackedEnsembleModel
foldChunkId() - Method in class hex.DataInfo
force_load_balance - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3: Increase training speed on small datasets by splitting it into many chunks to allow utilization of all cores.
forwardSolve(double[][], double[]) - Static method in class hex.util.LinearAlgebraUtils
fprop(long, boolean, int) - Method in class hex.deeplearning.Neurons.ExpRectifier
fprop(long, boolean, int) - Method in class hex.deeplearning.Neurons.ExpRectifierDropout
fprop(long, boolean, int) - Method in class hex.deeplearning.Neurons: Forward propagation
fprop(long, boolean, int) - Method in class hex.deeplearning.Neurons.Input
fprop(long, boolean, int) - Method in class hex.deeplearning.Neurons.Linear
fprop(long, boolean, int) - Method in class hex.deeplearning.Neurons.Maxout
fprop(long, boolean, int) - Method in class hex.deeplearning.Neurons.MaxoutDropout
fprop(long, boolean, int) - Method in class hex.deeplearning.Neurons.Rectifier
fprop(long, boolean, int) - Method in class hex.deeplearning.Neurons.RectifierDropout
fprop(long, boolean, int) - Method in class hex.deeplearning.Neurons.Softmax
fprop(long, boolean, int) - Method in class hex.deeplearning.Neurons.Tanh
fprop(long, boolean, int) - Method in class hex.deeplearning.Neurons.TanhDropout
fpropMiniBatch(long, Neurons[], DeepLearningModelInfo, DeepLearningModelInfo, boolean, double[], double[], int) - Static method in class hex.deeplearning.DeepLearningTask: Forward propagation assumption: layer 0 has _a filled with (horizontalized categoricals) double values
frame - Variable in class hex.schemas.DataInfoFrameV3
FrameTask<T extends FrameTask<T>> - Class in hex
FrameTask(Key<Job>, DataInfo) - Constructor for class hex.FrameTask
FrameTask(Key<Job>, DataInfo, long, int, boolean) - Constructor for class hex.FrameTask
FrameTask(Key<Job>, DataInfo, long, int, boolean, H2O.H2OCountedCompleter) - Constructor for class hex.FrameTask
FrameTask.ExtractDenseRow - Class in hex
FrameTask.ExtractDenseRow(DataInfo, long) - Constructor for class hex.FrameTask.ExtractDenseRow
FrameTask2<T extends FrameTask2<T>> - Class in hex: Created by tomasnykodym on 6/1/15.
FrameTask2(H2O.H2OCountedCompleter, DataInfo, Key<Job>) - Constructor for class hex.FrameTask2
FRESH - Static variable in class hex.tree.ScoreBuildHistogram
frobenius2(double[][]) - Static method in class hex.glrm.GLRM
fullCatOffsets() - Method in class hex.DataInfo
fullN() - Method in class hex.DataInfo: Get the fully expanded number of predictor columns.
fullN() - Method in class hex.gram.Gram
fullName() - Method in class hex.aggregator.AggregatorModel.AggregatorParameters
fullName() - Method in class hex.coxph.CoxPHModel.CoxPHParameters
fullName() - Method in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
fullName() - Method in class hex.deepwater.DeepWaterParameters
fullName() - Method in class hex.example.ExampleModel.ExampleParameters
fullName() - Method in class hex.glm.GLMModel.GLMParameters
fullName() - Method in class hex.glrm.GLRMModel.GLRMParameters
fullName() - Method in class hex.grep.GrepModel.GrepParameters
fullName() - Method in class hex.kmeans.KMeansModel.KMeansParameters
fullName() - Method in class hex.naivebayes.NaiveBayesModel.NaiveBayesParameters
fullName() - Method in class hex.pca.PCAModel.PCAParameters
fullName() - Method in class hex.StackedEnsembleModel.StackedEnsembleParameters
fullName() - Method in class hex.svd.SVDModel.SVDParameters
fullName() - Method in class hex.tree.drf.DRFModel.DRFParameters
fullName() - Method in class hex.tree.gbm.GBMModel.GBMParameters
fullName() - Method in class hex.word2vec.Word2VecModel.Word2VecParameters

G

gamma_x - Variable in class hex.schemas.GLRMV3.GLRMParametersV3
gamma_y - Variable in class hex.schemas.GLRMV3.GLRMParametersV3
GBM - Class in hex.tree.gbm: Gradient Boosted Trees Based on "Elements of Statistical Learning, Second Edition, page 387"
GBM(GBMModel.GBMParameters) - Constructor for class hex.tree.gbm.GBM
GBM(GBMModel.GBMParameters, Key<GBMModel>) - Constructor for class hex.tree.gbm.GBM
GBM(boolean) - Constructor for class hex.tree.gbm.GBM
GBM.DiffMinusMedianDiff - Class in hex.tree.gbm
GBM.DiffMinusMedianDiff(Vec, double[]) - Constructor for class hex.tree.gbm.GBM.DiffMinusMedianDiff
GBMModel - Class in hex.tree.gbm
GBMModel(Key<GBMModel>, GBMModel.GBMParameters, GBMModel.GBMOutput) - Constructor for class hex.tree.gbm.GBMModel
GBMModel.GBMOutput - Class in hex.tree.gbm
GBMModel.GBMOutput(GBM) - 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
GBMModelV3 - Class in hex.schemas
GBMModelV3() - Constructor for class hex.schemas.GBMModelV3
GBMModelV3.GBMModelOutputV3 - Class in hex.schemas
GBMModelV3.GBMModelOutputV3() - Constructor for class hex.schemas.GBMModelV3.GBMModelOutputV3
GbmMojoWriter - Class in hex.tree.gbm: MOJO support for GBM model.
GbmMojoWriter() - Constructor for class hex.tree.gbm.GbmMojoWriter
GbmMojoWriter(GBMModel) - Constructor for class hex.tree.gbm.GbmMojoWriter
GBMV3 - Class in hex.schemas
GBMV3() - Constructor for class hex.schemas.GBMV3
GBMV3.GBMParametersV3 - Class in hex.schemas
GBMV3.GBMParametersV3() - Constructor for class hex.schemas.GBMV3.GBMParametersV3
generateIPC(double[], double, double[], double[], double[]) - Static method in class hex.util.DimensionReductionUtils: This method will calculate the importance of principal components for PCA/GLRM methods.
generateSummary(Key, int) - Method in class hex.glm.GLMModel: Re-do the TwoDim table generation with updated model.
get(int) - Method in class hex.DataInfo.Row
get(int, int) - Method in class hex.deeplearning.Storage.DenseColMatrix
get(int, int) - Method in class hex.deeplearning.Storage.DenseRowMatrix
get(int) - Method in class hex.deeplearning.Storage.DenseVector
get(int, int) - Method in interface hex.deeplearning.Storage.Matrix
get(int, int) - Method in class hex.deeplearning.Storage.SparseRowMatrix
get(int, int, int) - Method in interface hex.deeplearning.Storage.Tensor
get(int) - Method in interface hex.deeplearning.Storage.Vector
get(int, int) - Method in class hex.gram.Gram
get_ada_dx_g(int) - Method in class hex.deeplearning.DeepLearningModelInfo
get_avg_activations(int) - Method in class hex.deeplearning.DeepLearningModelInfo
get_biases(int) - Method in class hex.deeplearning.DeepLearningModelInfo
get_biases_ada_dx_g(int) - Method in class hex.deeplearning.DeepLearningModelInfo
get_biases_momenta(int) - Method in class hex.deeplearning.DeepLearningModelInfo
get_global_beta_multinomial() - Method in class hex.glm.GLMModel.GLMOutput
get_params() - Method in class hex.coxph.CoxPHModel
get_params() - Method in class hex.deeplearning.DeepLearningModel: Get the parameters actually used for model building, not the user-given ones (_parms) They might differ since some defaults are filled in, and some invalid combinations are auto-disabled in modifyParams
get_params() - Method in class hex.deeplearning.DeepLearningModelInfo
get_params() - Method in class hex.deepwater.DeepWaterModel: Get the parameters actually used for model building, not the user-given ones (_parms) They might differ since some defaults are filled in, and some invalid combinations are auto-disabled in modifyParams
get_params() - Method in class hex.deepwater.DeepWaterModelInfo
get_processed_global() - Method in class hex.deeplearning.DeepLearningModelInfo
get_processed_local() - Method in class hex.deeplearning.DeepLearningModelInfo
get_processed_total() - Method in class hex.deeplearning.DeepLearningModelInfo
get_weights(int) - Method in class hex.deeplearning.DeepLearningModelInfo
get_weights_momenta(int) - Method in class hex.deeplearning.DeepLearningModelInfo
getBeta(double[]) - Method in class hex.glm.GLMModel.Submodel
getCat(int, int, int) - Method in class hex.glrm.GLRM.Archetypes
getCatBlock(int) - Method in class hex.glrm.GLRM.Archetypes
getCatCidx(int, int) - Method in class hex.glrm.GLRM.Archetypes
getCategoricalId(int, double) - Method in class hex.DataInfo
getCategoricalId(int, int) - Method in class hex.DataInfo: Get the offset into the expanded categorical
getCategoricalIdFromInteraction(int, int) - Method in class hex.DataInfo
getCheckpointNonModifiableFields() - Method in class hex.tree.SharedTreeModel.SharedTreeParameters
getChildNodeID(Chunk[], int) - Method in class hex.tree.DTree.DecidedNode
getDataInfoFrame(int, DataInfoFrameV3) - Method in class hex.api.MakeGLMModelHandler: Get the expanded (interactions + offsets) dataset.
getDecisionPath(double[]) - Method in class hex.tree.CompressedTree
getGlobalQuantilesKey(int) - Method in class hex.tree.SharedTree.Driver
getGlobalQuantilesKeys() - Method in class hex.tree.SharedTree.Driver
getGradient(double[]) - Method in class hex.glm.GLM.GLMGradientSolver
getGradient(double[]) - Method in class hex.glm.GLM.ProximalGradientSolver
getGradient(double[]) - Method in interface hex.optimization.OptimizationUtils.GradientSolver: Evaluate ginfo at solution beta.
getInitialValue() - Method in class hex.tree.SharedTree: Compute the inital value for a given distribution
getInstance() - Static method in class hex.deeplearning.MurmurHash
getInteractionOffset(Chunk[], int, int) - Method in class hex.DataInfo
getInv() - Method in class hex.gram.Gram.Cholesky
getInvDiag() - Method in class hex.gram.Gram.Cholesky
getL() - Method in class hex.gram.Gram.Cholesky
getL() - Method in class hex.gram.Gram.InPlaceCholesky
getMiniBatchSize() - Method in class hex.deeplearning.DeepLearningTask
getMiniBatchSize() - Method in class hex.FrameTask: Note: If this is overridden, then applyMiniBatch must be overridden as well to perform the model/weight mini-batch update
getModel() - Method in class hex.deepwater.DeepWaterModelInfo
getModelCategory() - Method in class hex.aggregator.AggregatorModel.AggregatorOutput
getModelCategory() - Method in class hex.deeplearning.DeepLearningModel.DeepLearningModelOutput
getModelCategory() - Method in class hex.deepwater.DeepWaterModelOutput
getModelCategory() - Method in class hex.example.ExampleModel.ExampleOutput
getModelCategory() - Method in class hex.glrm.GLRMModel.GLRMOutput
getModelCategory() - Method in class hex.grep.GrepModel.GrepOutput
getModelCategory() - Method in class hex.pca.PCAModel.PCAOutput
getModelCategory() - Method in class hex.svd.SVDModel.SVDOutput
getModelCategory() - Method in class hex.word2vec.Word2VecModel.Word2VecOutput
getMojo() - Method in class hex.deepwater.DeepWaterModel
getMojo() - Method in class hex.glm.GLMModel
getMojo() - Method in class hex.glrm.GLRMModel
getMojo() - Method in class hex.kmeans.KMeansModel
getMojo() - Method in class hex.tree.drf.DRFModel
getMojo() - Method in class hex.tree.gbm.GBMModel
getMojo() - Method in class hex.word2vec.Word2VecModel
getMostImportantFeatures(int) - Method in class hex.tree.SharedTreeModel
getName() - Method in class hex.api.RegisterAlgos
getNormBeta() - Method in class hex.glm.GLMModel.GLMOutput
getNormBetaMultinomial() - Method in class hex.glm.GLMModel.GLMOutput
getNormBetaMultinomial(int) - Method in class hex.glm.GLMModel.GLMOutput
getNum(int, int) - Method in class hex.glrm.GLRM.Archetypes
getNumCidx(int) - Method in class hex.glrm.GLRM.Archetypes
getObj() - Method in interface hex.optimization.OptimizationUtils.LineSearchSolver
getObj() - Method in class hex.optimization.OptimizationUtils.MoreThuente
getObj() - Method in class hex.optimization.OptimizationUtils.SimpleBacktrackingLS
getObjective(double[]) - Method in class hex.glm.GLM.GLMGradientSolver
getObjective(double[]) - Method in class hex.glm.GLM.ProximalGradientSolver
getObjective(double[]) - Method in interface hex.optimization.OptimizationUtils.GradientSolver
getOffsetVec() - Method in class hex.DataInfo
getOutput(int) - Method in class hex.DataInfo.Row
getOutputVec(int) - Method in class hex.DataInfo
getParams() - Method in class hex.word2vec.Word2VecModel.Word2VecModelInfo
getRegularizationPath() - Method in class hex.glm.GLMModel
getSearchDirection(double[], double[]) - Method in class hex.optimization.L_BFGS.History
getSubmodel(double) - Method in class hex.glm.GLMModel.GLMOutput
getToEigenVec() - Method in class hex.aggregator.Aggregator
getToEigenVec() - Method in class hex.aggregator.AggregatorModel
getToEigenVec() - Method in class hex.deeplearning.DeepLearning
getToEigenVec() - Method in class hex.deeplearning.DeepLearningModel
getToEigenVec() - Method in class hex.deepwater.DeepWater
getToEigenVec() - Method in class hex.deepwater.DeepWaterModel
getToEigenVec() - Method in class hex.kmeans.KMeans
getToEigenVec() - Method in class hex.kmeans.KMeansModel
getToEigenVec() - Method in class hex.tree.SharedTree
getToEigenVec() - Method in class hex.tree.SharedTreeModel
getWeightsVec() - Method in class hex.DataInfo
getX() - Method in interface hex.optimization.OptimizationUtils.LineSearchSolver
getX() - Method in class hex.optimization.OptimizationUtils.MoreThuente
getX() - Method in class hex.optimization.OptimizationUtils.SimpleBacktrackingLS
getXX() - Method in class hex.gram.Gram
getXX(boolean, boolean) - Method in class hex.gram.Gram
getXX(double[][]) - Method in class hex.gram.Gram
getXX(double[][], boolean, boolean) - Method in class hex.gram.Gram
getY(boolean) - Method in class hex.glrm.GLRM.Archetypes
ginfo() - Method in class hex.glm.ComputationState
ginfo - Variable in class hex.optimization.L_BFGS.Result
ginfo() - Method in interface hex.optimization.OptimizationUtils.LineSearchSolver
ginfo() - Method in class hex.optimization.OptimizationUtils.MoreThuente
ginfo() - Method in class hex.optimization.OptimizationUtils.SimpleBacktrackingLS
ginfoMultinomial(int) - Method in class hex.glm.ComputationState
GLM - Class in hex.glm: Created by tomasnykodym on 8/27/14.
GLM(boolean) - Constructor for class hex.glm.GLM
GLM(GLMModel.GLMParameters) - Constructor for class hex.glm.GLM
GLM(GLMModel.GLMParameters, Key) - Constructor for class hex.glm.GLM
GLM.BetaConstraint - Class in hex.glm
GLM.BetaConstraint() - Constructor for class hex.glm.GLM.BetaConstraint
GLM.BetaConstraint(Frame) - Constructor for class hex.glm.GLM.BetaConstraint
GLM.GLMDriver - Class in hex.glm: Main loop of the glm algo.
GLM.GLMDriver() - Constructor for class hex.glm.GLM.GLMDriver
GLM.GLMGradientInfo - Class in hex.glm
GLM.GLMGradientInfo(double, double, double[]) - Constructor for class hex.glm.GLM.GLMGradientInfo
GLM.GLMGradientSolver - Class in hex.glm: Gradient and line search computation for L_BFGS and also L_BFGS solver wrapper (for ADMM)
GLM.GLMGradientSolver(Job, GLMModel.GLMParameters, DataInfo, double, GLM.BetaConstraint) - Constructor for class hex.glm.GLM.GLMGradientSolver
GLM.GramSolver - Class in hex.glm: Created by tomasnykodym on 3/30/15.
GLM.GramSolver(Gram, double[], double, double, boolean) - Constructor for class hex.glm.GLM.GramSolver
GLM.GramSolver(Gram, double[], boolean, double, double, double[], double[], double[], double[]) - Constructor for class hex.glm.GLM.GramSolver
GLM.ProximalGradientInfo - Class in hex.glm
GLM.ProximalGradientInfo(OptimizationUtils.GradientInfo, double, double[]) - Constructor for class hex.glm.GLM.ProximalGradientInfo
GLM.ProximalGradientSolver - Class in hex.glm: Simple wrapper around ginfo computation, adding proximal penalty
GLM.ProximalGradientSolver(OptimizationUtils.GradientSolver, double[], double[], double, double, OptimizationUtils.GradientInfo, L_BFGS.ProgressMonitor) - Constructor for class hex.glm.GLM.ProximalGradientSolver
GLMMetricBuilder - Class in hex.glm: Class for GLMValidation.
GLMMetricBuilder(String[], double[], GLMModel.GLMWeightsFun, int, boolean, boolean) - Constructor for class hex.glm.GLMMetricBuilder
GLMModel - Class in hex.glm: Created by tomasnykodym on 8/27/14.
GLMModel(Key, GLMModel.GLMParameters, GLM, double[], double, double, long) - Constructor for class hex.glm.GLMModel
GLMModel.GLMOutput - Class in hex.glm
GLMModel.GLMOutput(DataInfo, String[], String[][], String[], boolean) - Constructor for class hex.glm.GLMModel.GLMOutput
GLMModel.GLMOutput(DataInfo, String[], String[][], String[], boolean, double[]) - Constructor for class hex.glm.GLMModel.GLMOutput
GLMModel.GLMOutput() - Constructor for class hex.glm.GLMModel.GLMOutput
GLMModel.GLMOutput(GLM) - Constructor for class hex.glm.GLMModel.GLMOutput
GLMModel.GLMParameters - Class in hex.glm
GLMModel.GLMParameters() - Constructor for class hex.glm.GLMModel.GLMParameters
GLMModel.GLMParameters(GLMModel.GLMParameters.Family) - Constructor for class hex.glm.GLMModel.GLMParameters
GLMModel.GLMParameters(GLMModel.GLMParameters.Family, GLMModel.GLMParameters.Link) - Constructor for class hex.glm.GLMModel.GLMParameters
GLMModel.GLMParameters(GLMModel.GLMParameters.Family, GLMModel.GLMParameters.Link, double[], double[], double, double) - Constructor for class hex.glm.GLMModel.GLMParameters
GLMModel.GLMParameters(GLMModel.GLMParameters.Family, GLMModel.GLMParameters.Link, double[], double[], double, double, String[]) - 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.GLMWeights - Class in hex.glm
GLMModel.GLMWeights() - Constructor for class hex.glm.GLMModel.GLMWeights
GLMModel.GLMWeightsFun - Class in hex.glm
GLMModel.GLMWeightsFun(GLMModel.GLMParameters) - Constructor for class hex.glm.GLMModel.GLMWeightsFun
GLMModel.GLMWeightsFun(GLMModel.GLMParameters.Family, GLMModel.GLMParameters.Link, double, double) - Constructor for class hex.glm.GLMModel.GLMWeightsFun
GLMModel.RegularizationPath - Class in hex.glm
GLMModel.RegularizationPath() - Constructor for class hex.glm.GLMModel.RegularizationPath
GLMModel.Submodel - Class in hex.glm
GLMModel.Submodel(double, double[], int, double, double) - Constructor for class hex.glm.GLMModel.Submodel
GLMModelV3 - Class in hex.schemas
GLMModelV3() - Constructor for class hex.schemas.GLMModelV3
GLMModelV3.GLMModelOutputV3 - Class in hex.schemas
GLMModelV3.GLMModelOutputV3() - Constructor for class hex.schemas.GLMModelV3.GLMModelOutputV3
GLMMojoWriter - Class in hex.glm
GLMMojoWriter() - Constructor for class hex.glm.GLMMojoWriter
GLMMojoWriter(GLMModel) - Constructor for class hex.glm.GLMMojoWriter
GLMRegularizationPathV3 - Class in hex.schemas
GLMRegularizationPathV3() - Constructor for class hex.schemas.GLMRegularizationPathV3
GLMScore - Class in hex.glm: Created by tomas on 3/15/16.
GLMScore(Job, GLMModel, DataInfo, String[], boolean, boolean) - Constructor for class hex.glm.GLMScore
GLMTask - Class in hex.glm: All GLM related distributed tasks: YMUTask - computes response means on actual datasets (if some rows are ignored - e.g ignoring rows with NA and/or doing cross-validation) GLMGradientTask - computes gradient at given Beta, used by L-BFGS, for KKT condition check GLMLineSearchTask - computes residual deviance(s) at given beta(s), used by line search (both L-BFGS and IRLSM) GLMIterationTask - used by IRLSM to compute Gram matrix and response t(X) W X, t(X)Wz
GLMTask() - Constructor for class hex.glm.GLMTask
GLMTask.ComputeSETsk - Class in hex.glm
GLMTask.ComputeSETsk(H2O.H2OCountedCompleter, DataInfo, Key, double[], GLMModel.GLMParameters) - Constructor for class hex.glm.GLMTask.ComputeSETsk
GLMTask.GLMCoordinateDescentTaskSeqIntercept - Class in hex.glm
GLMTask.GLMCoordinateDescentTaskSeqIntercept(double[], DataInfo) - Constructor for class hex.glm.GLMTask.GLMCoordinateDescentTaskSeqIntercept
GLMTask.GLMCoordinateDescentTaskSeqNaive - Class in hex.glm
GLMTask.GLMCoordinateDescentTaskSeqNaive(boolean, boolean, int, double[], double[], int[], int[], double[], double[], double[], double[], boolean) - Constructor for class hex.glm.GLMTask.GLMCoordinateDescentTaskSeqNaive
GLMTask.GLMGenerateWeightsTask - Class in hex.glm
GLMTask.GLMGenerateWeightsTask(Key, DataInfo, GLMModel.GLMParameters, double[]) - Constructor for class hex.glm.GLMTask.GLMGenerateWeightsTask
GLMTask.GLMIterationTask - Class in hex.glm: One iteration of glm, computes weighted gram matrix and t(x)*y vector and t(y)*y scalar.
GLMTask.GLMIterationTask(Key, DataInfo, GLMModel.GLMWeightsFun, double[]) - Constructor for class hex.glm.GLMTask.GLMIterationTask
GLMTask.GLMIterationTask(Key, DataInfo, GLMModel.GLMWeightsFun, double[], int) - Constructor for class hex.glm.GLMTask.GLMIterationTask
GLMTask.GLMIterationTaskMultinomial - Class in hex.glm
GLMTask.GLMIterationTaskMultinomial(DataInfo, Key, double[], int) - Constructor for class hex.glm.GLMTask.GLMIterationTaskMultinomial
GLMTask.GLMMultinomialUpdate - Class in hex.glm
GLMTask.GLMMultinomialUpdate(DataInfo, Key, double[], int) - Constructor for class hex.glm.GLMTask.GLMMultinomialUpdate
GLMTask.GLMMultinomialWLSTask - Class in hex.glm
GLMTask.GLMMultinomialWLSTask(H2O.H2OCountedCompleter, DataInfo, Key, GLMModel.GLMWeightsFun, double[]) - Constructor for class hex.glm.GLMTask.GLMMultinomialWLSTask
GLMTask.GLMWLSTask - Class in hex.glm
GLMTask.GLMWLSTask(H2O.H2OCountedCompleter, DataInfo, Key, GLMModel.GLMWeightsFun, double[]) - Constructor for class hex.glm.GLMTask.GLMWLSTask
GLMTask.LSTask - Class in hex.glm: Task to compute t(X) %*% W %*% X and t(X) %*% W %*% y
GLMTask.LSTask(H2O.H2OCountedCompleter, DataInfo, Key) - Constructor for class hex.glm.GLMTask.LSTask
GLMTask.YMUTask - Class in hex.glm
GLMTask.YMUTask(DataInfo, int, boolean, boolean, boolean, boolean) - Constructor for class hex.glm.GLMTask.YMUTask
GLMV3 - Class in hex.schemas: Created by tomasnykodym on 8/29/14.
GLMV3() - Constructor for class hex.schemas.GLMV3
GLMV3.GLMParametersV3 - Class in hex.schemas
GLMV3.GLMParametersV3() - Constructor for class hex.schemas.GLMV3.GLMParametersV3
GLRM - Class in hex.glrm: Generalized Low Rank Models This is an algorithm for dimensionality reduction of a dataset.
GLRM(GLRMModel.GLRMParameters) - Constructor for class hex.glrm.GLRM
GLRM(GLRMModel.GLRMParameters, Job<GLRMModel>) - Constructor for class hex.glrm.GLRM
GLRM(boolean) - Constructor for class hex.glrm.GLRM
GLRM.Archetypes - Class in hex.glrm
GLRMModel - Class in hex.glrm: GLRM (Generalized Low Rank Model).
GLRMModel(Key<GLRMModel>, GLRMModel.GLRMParameters, GLRMModel.GLRMOutput) - Constructor for class hex.glrm.GLRMModel
GLRMModel.GLRMOutput - Class in hex.glrm
GLRMModel.GLRMOutput(GLRM) - Constructor for class hex.glrm.GLRMModel.GLRMOutput
GLRMModel.GLRMParameters - Class in hex.glrm
GLRMModel.GLRMParameters() - Constructor for class hex.glrm.GLRMModel.GLRMParameters
GLRMModelV3 - Class in hex.schemas
GLRMModelV3() - Constructor for class hex.schemas.GLRMModelV3
GLRMModelV3.GLRMModelOutputV3 - Class in hex.schemas
GLRMModelV3.GLRMModelOutputV3() - Constructor for class hex.schemas.GLRMModelV3.GLRMModelOutputV3
GlrmMojoWriter - Class in hex.glrm: MOJO serializer for GLRM model.
GlrmMojoWriter() - Constructor for class hex.glrm.GlrmMojoWriter
GlrmMojoWriter(GLRMModel) - Constructor for class hex.glrm.GlrmMojoWriter
GLRMV3 - Class in hex.schemas
GLRMV3() - Constructor for class hex.schemas.GLRMV3
GLRMV3.GLRMParametersV3 - Class in hex.schemas
GLRMV3.GLRMParametersV3() - Constructor for class hex.schemas.GLRMV3.GLRMParametersV3
gpu - Variable in class hex.schemas.DeepWaterV3.DeepWaterParametersV3
gradient(double[]) - Method in class hex.glm.GLM.GramSolver
gradient(double[]) - Method in class hex.glm.GLM.ProximalGradientSolver
gradient(double[]) - Method in interface hex.optimization.ADMM.ProximalSolver
gradient_epsilon - Variable in class hex.schemas.GLMV3.GLMParametersV3
gradientCheck - Static variable in class hex.deeplearning.DeepLearningModelInfo
gradientCheckBias - Static variable in class hex.deeplearning.DeepLearningModelInfo
Gram - Class in hex.gram
Gram(DataInfo) - Constructor for class hex.gram.Gram
Gram(int, int, int, int, boolean) - Constructor for class hex.gram.Gram
Gram.Cholesky - Class in hex.gram
Gram.Cholesky(double[][], double[]) - Constructor for class hex.gram.Gram.Cholesky
Gram.Cholesky(double[][], double[], boolean) - Constructor for class hex.gram.Gram.Cholesky
Gram.CollinearColumnsException - Exception in hex.gram
Gram.CollinearColumnsException() - Constructor for exception hex.gram.Gram.CollinearColumnsException
Gram.CollinearColumnsException(String) - Constructor for exception hex.gram.Gram.CollinearColumnsException
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<Job>, DataInfo) - Constructor for class hex.gram.Gram.GramTask
Gram.GramTask(Key<Job>, 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
Gram.NonSPDMatrixException(String) - Constructor for exception hex.gram.Gram.NonSPDMatrixException
Gram.OuterGramTask - Class in hex.gram: Task to compute outer product of a matrix normalized by the number of observations (not counting rows with NAs).
Gram.OuterGramTask(Key<Job>, DataInfo) - Constructor for class hex.gram.Gram.OuterGramTask
GramV3 - Class in hex.schemas: Created by tomas on 10/26/16.
GramV3() - Constructor for class hex.schemas.GramV3
Grep - Class in hex.grep: Grep model builder...
Grep(GrepModel.GrepParameters) - Constructor for class hex.grep.Grep
GrepModel - Class in hex.grep
GrepModel.GrepOutput - Class in hex.grep
GrepModel.GrepOutput(Grep) - Constructor for class hex.grep.GrepModel.GrepOutput
GrepModel.GrepParameters - Class in hex.grep
GrepModel.GrepParameters() - Constructor for class hex.grep.GrepModel.GrepParameters
GrepModelV3 - Class in hex.schemas
GrepModelV3() - Constructor for class hex.schemas.GrepModelV3
GrepModelV3.GrepModelOutputV3 - Class in hex.schemas
GrepModelV3.GrepModelOutputV3() - Constructor for class hex.schemas.GrepModelV3.GrepModelOutputV3
GrepV3 - Class in hex.schemas
GrepV3() - Constructor for class hex.schemas.GrepV3
GrepV3.GrepParametersV3 - Class in hex.schemas
GrepV3.GrepParametersV3() - Constructor for class hex.schemas.GrepV3.GrepParametersV3
gslvr() - Method in class hex.glm.ComputationState
gslvrMultinomial(int) - Method in class hex.glm.ComputationState

H

handlesSparseData() - Method in class hex.FrameTask2
handlesSparseData() - Method in class hex.glm.GLMTask.GLMIterationTask
hasBounds() - Method in class hex.glm.GLM.BetaConstraint
hasClosedForm(long) - Method in class hex.glrm.GLRM
hasGradient() - Method in class hex.glm.GLM.GramSolver
hasGradient() - Method in class hex.glm.GLM.ProximalGradientSolver
hasGradient() - Method in interface hex.optimization.ADMM.ProximalSolver
hash(byte[], int, int) - Method in class hex.deeplearning.MurmurHash
hashCode() - Method in class hex.deepwater.DeepWaterModelInfo
hasNaNsOrInf() - Method in class hex.glm.GLMTask.GLMIterationTask
hasNaNsOrInfs() - Method in class hex.gram.Gram
hasProximalPenalty() - Method in class hex.glm.GLM.BetaConstraint
hasPValues() - Method in class hex.glm.GLMModel.GLMOutput
haveBackend() - Static method in class hex.deepwater.DeepWater: Check whether we have any Deep Water native backends available
haveMojo() - Method in class hex.deeplearning.DeepLearning
haveMojo() - Method in class hex.deepwater.DeepWater
haveMojo() - Method in class hex.glm.GLM
haveMojo() - Method in class hex.glrm.GLRM
haveMojo() - Method in class hex.kmeans.KMeans
haveMojo() - Method in class hex.naivebayes.NaiveBayes
haveMojo() - Method in class hex.pca.PCA
haveMojo() - Method in class hex.svd.SVD
haveMojo() - Method in class hex.tree.SharedTree
haveMojo() - Method in class hex.word2vec.Word2Vec
havePojo() - Method in class hex.deeplearning.DeepLearning
havePojo() - Method in class hex.deepwater.DeepWater
havePojo() - Method in class hex.glm.GLM
havePojo() - Method in class hex.glrm.GLRM
havePojo() - Method in class hex.kmeans.KMeans
havePojo() - Method in class hex.naivebayes.NaiveBayes
havePojo() - Method in class hex.pca.PCA
havePojo() - Method in class hex.svd.SVD
havePojo() - Method in class hex.tree.SharedTree
hex - package hex
hex.aggregator - package hex.aggregator
hex.api - package hex.api
hex.coxph - package hex.coxph
hex.deeplearning - package hex.deeplearning
hex.deepwater - package hex.deepwater
hex.ensemble - package hex.ensemble
hex.example - package hex.example
hex.glm - package hex.glm
hex.glrm - package hex.glrm
hex.gram - package hex.gram
hex.grep - package hex.grep
hex.kmeans - package hex.kmeans
hex.naivebayes - package hex.naivebayes
hex.optimization - package hex.optimization
hex.pca - package hex.pca
hex.schemas - package hex.schemas
hex.splitframe - package hex.splitframe
hex.svd - package hex.svd
hex.tree - package hex.tree
hex.tree.drf - package hex.tree.drf
hex.tree.gbm - package hex.tree.gbm
hex.util - package hex.util
hex.word2vec - package hex.word2vec
hidden - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3: The number and size of each hidden layer in the model.
hidden - Variable in class hex.schemas.DeepWaterV3.DeepWaterParametersV3: The number and size of each hidden layer in the model.
hidden_dropout_ratios - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3: A fraction of the inputs for each hidden layer to be omitted from training in order to improve generalization.
hidden_dropout_ratios - Variable in class hex.schemas.DeepWaterV3.DeepWaterParametersV3: A fraction of the inputs for each hidden layer to be omitted from training in order to improve generalization.
histogram_type - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3

I

idx_nids(int) - Method in class hex.tree.SharedTree
idx_offset() - Method in class hex.tree.SharedTree
idx_oobt() - Method in class hex.tree.SharedTree
idx_resp() - Method in class hex.tree.SharedTree
idx_tree(int) - Method in class hex.tree.SharedTree
idx_weight() - Method in class hex.tree.SharedTree
idx_work(int) - Method in class hex.tree.SharedTree
idx_xnew(int, int, int) - Static method in class hex.glrm.GLRM
idx_xold(int, int) - Static method in class hex.glrm.GLRM
idxs - Variable in class hex.glm.GLMModel.Submodel
ignoreBadColumns(int, boolean) - Method in class hex.word2vec.Word2Vec
ignoreInvalidColumns(int, boolean) - Method in class hex.tree.SharedTree
ignoreStringColumns() - Method in class hex.deepwater.DeepWater
image_shape - Variable in class hex.schemas.DeepWaterV3.DeepWaterParametersV3
imp(T) - Method in class hex.tree.drf.TreeMeasuresCollector.TreeMeasures: Compute variable importance with respect to given votes.
imp(TreeMeasuresCollector.TreeSSE) - Method in class hex.tree.drf.TreeMeasuresCollector.TreeSSE
imp(TreeMeasuresCollector.TreeVotes) - Method in class hex.tree.drf.TreeMeasuresCollector.TreeVotes: Compute variable importance with respect to given votes.
importance - Variable in class hex.schemas.GLRMModelV3.GLRMModelOutputV3
importance - Variable in class hex.schemas.PCAModelV3.PCAModelOutputV3
impute_missing - Variable in class hex.schemas.PCAV3.PCAParametersV3
impute_original - Variable in class hex.schemas.GLRMV3.GLRMParametersV3
imputeCat(Vec) - Static method in class hex.DataInfo
imputeCat(Vec, boolean) - Static method in class hex.DataInfo
incr0(int, double, double) - Method in class hex.tree.DHistogram
incr1(int, double, double) - Method in class hex.tree.DHistogram
init(boolean) - Method in class hex.aggregator.Aggregator
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, DeepLearningModelInfo, boolean) - Method in class hex.deeplearning.Neurons: Initialization of the parameters and connectivity of a Neuron layer
init(boolean) - Method in class hex.deepwater.DeepWater: Initialize the ModelBuilder, validating all arguments and preparing the training frame.
init(boolean) - Method in class hex.example.Example: Initialize the ModelBuilder, validating all arguments and preparing the training frame.
init(boolean) - Method in class hex.glm.GLM
init(boolean) - Method in class hex.glrm.GLRM: Validate all parameters, and prepare the model for training.
init(boolean) - Method in class hex.grep.Grep: Initialize the ModelBuilder, validating all arguments and preparing the training frame.
init(boolean) - Method in class hex.kmeans.KMeans: Initialize the ModelBuilder, validating all arguments and preparing the training frame.
init(boolean) - Method in class hex.naivebayes.NaiveBayes
init(boolean) - Method in class hex.pca.PCA
init - Variable in class hex.schemas.GLRMV3.GLRMParametersV3
init - Variable in class hex.schemas.KMeansV3.KMeansParametersV3
init(boolean) - Method in class hex.svd.SVD
init() - Method in class hex.tree.DHistogram
init(double[]) - Method in class hex.tree.DHistogram
init(boolean) - Method in class hex.tree.drf.DRF: Initialize the ModelBuilder, validating all arguments and preparing the training frame.
init(boolean) - Method in class hex.tree.gbm.GBM: Initialize the ModelBuilder, validating all arguments and preparing the training frame.
init(boolean) - Method in class hex.tree.SharedTree: Initialize the ModelBuilder, validating all arguments and preparing the training frame.
init(boolean) - Method in class hex.word2vec.Word2Vec: Initialize the ModelBuilder, validating all arguments and preparing the training frame.
init_learning_rate - Variable in class hex.schemas.Word2VecV3.Word2VecParametersV3
init_step_size - Variable in class hex.schemas.GLRMV3.GLRMParametersV3
initial_biases - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
initial_weight_distribution - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3: The distribution from which initial weights are to be drawn.
initial_weight_scale - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3: The scale of the distribution function for Uniform or Normal distributions.
initial_weights - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
initialHist(Frame, int, int, DHistogram[], long, SharedTreeModel.SharedTreeParameters, Key[]) - Static method in class hex.tree.DHistogram
initializeModelSpecifics() - Method in class hex.tree.SharedTree.Driver
initStats(CoxPHModel, DataInfo) - Method in class hex.coxph.CoxPH.CoxPHDriver
innerProduct(double[]) - Method in class hex.DataInfo.Row
innerProduct(double[], boolean) - Method in class hex.DataInfo.Row
innerProductChunk(DataInfo.Row, DataInfo.Row, Chunk[], Chunk[]) - Method in class hex.gram.Gram.OuterGramTask
input_dropout_ratio - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3: A fraction of the features for each training row to be omitted from training in order to improve generalization (dimension sampling).
input_dropout_ratio - Variable in class hex.schemas.DeepWaterV3.DeepWaterParametersV3: A fraction of the features for each training row to be omitted from training in order to improve generalization (dimension sampling).
interactions() - Method in class hex.glm.GLMModel.GLMOutput
interactions - Variable in class hex.schemas.DataInfoFrameV3
interactions - Variable in class hex.schemas.GLMV3.GLMParametersV3
interactions_only - Variable in class hex.schemas.DataInfoFrameV3
intercept - Variable in class hex.schemas.GLMV3.GLMParametersV3
isAutoencoder() - Method in class hex.deeplearning.DeepLearningModel.DeepLearningModelOutput
isAutoencoder() - Method in class hex.deepwater.DeepWaterModelOutput
isBad() - Method in class hex.DataInfo.Row
isDecidedRow(int) - Static method in class hex.tree.ScoreBuildHistogram
isInteractionVec(int) - Method in class hex.DataInfo
isMeanAdjusted() - Method in enum hex.DataInfo.TransformType
isOOBRow(int) - Static method in class hex.tree.ScoreBuildHistogram
isRootNode(DTree.Node) - Static method in class hex.tree.DTree
isSigmaScaled() - Method in enum hex.DataInfo.TransformType
isSparse() - Method in class hex.DataInfo.Row
isSPD() - Method in class hex.gram.Gram.Cholesky
isSPD() - Method in class hex.gram.Gram.InPlaceCholesky
isStandardized() - Method in class hex.glm.GLMModel.GLMOutput
isSupervised() - Method in class hex.aggregator.Aggregator
isSupervised() - Method in class hex.coxph.CoxPH
isSupervised() - Method in class hex.deeplearning.DeepLearning
isSupervised() - Method in class hex.deeplearning.DeepLearningModel.DeepLearningModelOutput
isSupervised() - Method in class hex.deepwater.DeepWater
isSupervised() - Method in class hex.deepwater.DeepWaterModelOutput
isSupervised() - Method in class hex.ensemble.StackedEnsemble
isSupervised() - Method in class hex.example.Example
isSupervised() - Method in class hex.glm.GLM
isSupervised() - Method in class hex.glm.GLMModel.GLMOutput
isSupervised() - Method in class hex.glrm.GLRM
isSupervised() - Method in class hex.grep.Grep
isSupervised() - Method in class hex.naivebayes.NaiveBayes
isSupervised() - Method in class hex.pca.PCA
isSupervised() - Method in class hex.svd.SVD
isSupervised() - Method in class hex.tree.SharedTree
isSupervised() - Method in class hex.word2vec.Word2Vec
isUnstable() - Method in class hex.deeplearning.DeepLearningModelInfo
isValid() - Method in class hex.optimization.OptimizationUtils.GradientInfo
isValid() - Method in class hex.tree.TreeStats
iter() - Method in class hex.glm.GLM.GramSolver
iter() - Method in class hex.glm.GLM.ProximalGradientSolver
iter() - Method in interface hex.optimization.ADMM.ProximalSolver
iter - Variable in class hex.optimization.L_BFGS.Result
iter_max - Variable in class hex.coxph.CoxPHModel.CoxPHParameters
iteration - Variable in class hex.glm.GLMModel.Submodel
iterations - Variable in class hex.deeplearning.DeepLearningModel
iterations - Variable in class hex.deeplearning.DeepLearningScoringInfo
iterations() - Method in class hex.deeplearning.DeepLearningScoringInfo
iterations() - Method in class hex.deepwater.DeepWaterScoringInfo
iterations - Variable in class hex.schemas.ExampleModelV3.ExampleModelOutputV3
iterations - Variable in class hex.schemas.GLRMModelV3.GLRMModelOutputV3

J

javaName() - Method in class hex.aggregator.AggregatorModel.AggregatorParameters
javaName() - Method in class hex.coxph.CoxPHModel.CoxPHParameters
javaName() - Method in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
javaName() - Method in class hex.deepwater.DeepWaterParameters
javaName() - Method in class hex.example.ExampleModel.ExampleParameters
javaName() - Method in class hex.glm.GLMModel.GLMParameters
javaName() - Method in class hex.glrm.GLRMModel.GLRMParameters
javaName() - Method in class hex.grep.GrepModel.GrepParameters
javaName() - Method in class hex.kmeans.KMeansModel.KMeansParameters
javaName() - Method in class hex.naivebayes.NaiveBayesModel.NaiveBayesParameters
javaName() - Method in class hex.pca.PCAModel.PCAParameters
javaName() - Method in class hex.StackedEnsembleModel.StackedEnsembleParameters
javaName() - Method in class hex.svd.SVDModel.SVDParameters
javaName() - Method in class hex.tree.drf.DRFModel.DRFParameters
javaName() - Method in class hex.tree.gbm.GBMModel.GBMParameters
javaName() - Method in class hex.word2vec.Word2VecModel.Word2VecParameters

K

k() - Method in class hex.optimization.L_BFGS
k - Variable in class hex.schemas.AggregatorV99.AggregatorParametersV99
k - Variable in class hex.schemas.GLRMV3.GLRMParametersV3
k - Variable in class hex.schemas.PCAV3.PCAParametersV3
keep_u - Variable in class hex.schemas.SVDV99.SVDParametersV99
KMeans - Class in hex.kmeans: Scalable K-Means++ (KMeans||)
http://theory.stanford.edu/~sergei/papers/vldb12-kmpar.pdf
http://www.youtube.com/watch?v=cigXAxV3XcY
KMeans(KMeansModel.KMeansParameters) - Constructor for class hex.kmeans.KMeans
KMeans(KMeansModel.KMeansParameters, Job) - Constructor for class hex.kmeans.KMeans
KMeans(boolean) - Constructor for class hex.kmeans.KMeans
KMeans.Initialization - Enum in hex.kmeans
KMeansModel - Class in hex.kmeans
KMeansModel(Key, KMeansModel.KMeansParameters, KMeansModel.KMeansOutput) - Constructor for class hex.kmeans.KMeansModel
KMeansModel.KMeansOutput - Class in hex.kmeans
KMeansModel.KMeansOutput(KMeans) - Constructor for class hex.kmeans.KMeansModel.KMeansOutput
KMeansModel.KMeansParameters - Class in hex.kmeans
KMeansModel.KMeansParameters() - Constructor for class hex.kmeans.KMeansModel.KMeansParameters
KMeansModelV3 - Class in hex.schemas
KMeansModelV3() - Constructor for class hex.schemas.KMeansModelV3
KMeansModelV3.KMeansModelOutputV3 - Class in hex.schemas
KMeansModelV3.KMeansModelOutputV3() - Constructor for class hex.schemas.KMeansModelV3.KMeansModelOutputV3
KMeansMojoWriter - Class in hex.kmeans
KMeansMojoWriter() - Constructor for class hex.kmeans.KMeansMojoWriter
KMeansMojoWriter(KMeansModel) - Constructor for class hex.kmeans.KMeansMojoWriter
KMeansV3 - Class in hex.schemas
KMeansV3() - Constructor for class hex.schemas.KMeansV3
KMeansV3.KMeansParametersV3 - Class in hex.schemas
KMeansV3.KMeansParametersV3() - Constructor for class hex.schemas.KMeansV3.KMeansParametersV3

L

l - Variable in class hex.glm.GLMModel.GLMWeights
l1 - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3: A regularization method that constrains the absolute value of the weights and has the net effect of dropping some weights (setting them to zero) from a model to reduce complexity and avoid overfitting.
l1pen() - Method in class hex.glm.ComputationState
l2 - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3: A regularization method that constrains the sum of the squared weights.
l2pen() - Method in class hex.glm.ComputationState
L_BFGS - Class in hex.optimization: Created by tomasnykodym on 9/15/14.
L_BFGS() - Constructor for class hex.optimization.L_BFGS
L_BFGS.History - Class in hex.optimization: Keeps L-BFGS history ie curvature information recorded over the last m steps.
L_BFGS.History(int, int) - Constructor for class hex.optimization.L_BFGS.History
L_BFGS.ProgressMonitor - Interface in hex.optimization: Monitor progress and enable early termination.
L_BFGS.Result - Class in hex.optimization
L_BFGS.Result(boolean, int, double[], OptimizationUtils.GradientInfo, double) - Constructor for class hex.optimization.L_BFGS.Result
lambda() - Method in class hex.glm.ComputationState
lambda - Variable in class hex.schemas.GLMV3.GLMParametersV3
lambda_1se() - Method in class hex.glm.GLMModel.GLMOutput
lambda_best() - Method in class hex.glm.GLMModel.GLMOutput
lambda_min_ratio - Variable in class hex.schemas.GLMV3.GLMParametersV3
lambda_search - Variable in class hex.schemas.GLMV3.GLMParametersV3
lambda_selected() - Method in class hex.glm.GLMModel.GLMOutput
lambda_value - Variable in class hex.glm.GLMModel.Submodel
lambdas - Variable in class hex.schemas.GLMRegularizationPathV3
laplace - Variable in class hex.schemas.NaiveBayesV3.NaiveBayesParametersV3
largestCat() - Method in class hex.DataInfo
last_scored() - Method in class hex.deeplearning.DeepLearningModel
last_scored() - Method in class hex.deepwater.DeepWaterModel
leaf(float) - Method in class hex.tree.TreeVisitor
learn_rate - Variable in class hex.schemas.GBMV3.GBMParametersV3
learn_rate_annealing - Variable in class hex.schemas.GBMV3.GBMParametersV3
learning_rate - Variable in class hex.schemas.DeepWaterV3.DeepWaterParametersV3: 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.
learning_rate_annealing - Variable in class hex.schemas.DeepWaterV3.DeepWaterParametersV3: Learning rate annealing reduces the learning rate to "freeze" into local minima in the optimization landscape.
learningRate(double) - Method in class hex.deepwater.DeepWaterParameters
len() - Method in class hex.tree.DTree
levels - Variable in class hex.schemas.NaiveBayesModelV3.NaiveBayesModelOutputV3
likelihood() - Method in class hex.glm.ComputationState
likelihood(double, double) - Method in class hex.glm.GLMModel.GLMParameters
likelihood(double, double) - Method in class hex.glm.GLMModel.GLMWeightsFun
likelihoodAndDeviance(double, GLMModel.GLMWeights, double) - Method in class hex.glm.GLMModel.GLMWeightsFun
LinearAlgebraUtils - Class in hex.util
LinearAlgebraUtils() - Constructor for class hex.util.LinearAlgebraUtils
LinearAlgebraUtils.BMulInPlaceTask - Class in hex.util: Computes B = XY where X is n by k and Y is k by p, saving result in same frame Input: [X,B] (large frame) passed to doAll, where we write to B yt = Y' = transpose of Y (small matrix) ncolX = number of columns in X
LinearAlgebraUtils.BMulInPlaceTask(DataInfo, double[][]) - Constructor for class hex.util.LinearAlgebraUtils.BMulInPlaceTask
LinearAlgebraUtils.BMulInPlaceTask(DataInfo, double[][], int) - Constructor for class hex.util.LinearAlgebraUtils.BMulInPlaceTask
LinearAlgebraUtils.BMulTask - Class in hex.util: Computes B = XY where X is n by k and Y is k by p, saving result in new vecs Input: dinfo = X (large frame) with dinfo._adaptedFrame passed to doAll yt = Y' = transpose of Y (small matrix) Output: XY (large frame) is n by p
LinearAlgebraUtils.BMulTask(Key<Job>, DataInfo, double[][]) - Constructor for class hex.util.LinearAlgebraUtils.BMulTask
LinearAlgebraUtils.ForwardSolve - Class in hex.util: Given lower triangular L, solve for Q in QL' = A (LQ' = A') using forward substitution Dimensions: A is n by p, Q is n by p, R = L' is p by p Input: [A,Q] (large frame) passed to doAll, where we write to Q
LinearAlgebraUtils.ForwardSolve(DataInfo, double[][]) - Constructor for class hex.util.LinearAlgebraUtils.ForwardSolve
LinearAlgebraUtils.ForwardSolveInPlace - Class in hex.util: Given lower triangular L, solve for Q in QL' = A (LQ' = A') using forward substitution Dimensions: A is n by p, Q is n by p, R = L' is p by p Input: A (large frame) passed to doAll, where we overwrite each row of A with its row of Q
LinearAlgebraUtils.ForwardSolveInPlace(DataInfo, double[][]) - Constructor for class hex.util.LinearAlgebraUtils.ForwardSolveInPlace
LinearAlgebraUtils.SMulTask - Class in hex.util: Computes A'Q where A is n by p and Q is n by k Input: [A,Q] (large frame) passed to doAll Output: atq = A'Q (small matrix) is \tilde{p} by k where \tilde{p} = number of cols in A with categoricals expanded
LinearAlgebraUtils.SMulTask(DataInfo, int) - Constructor for class hex.util.LinearAlgebraUtils.SMulTask
LinearAlgebraUtils.SMulTask(DataInfo, int, int) - Constructor for class hex.util.LinearAlgebraUtils.SMulTask
link(double) - Method in class hex.glm.GLMModel.GLMWeightsFun
link - Variable in class hex.schemas.GLMV3.GLMParametersV3
linkDeriv(double) - Method in class hex.glm.GLMModel.GLMParameters
linkDeriv(double) - Method in class hex.glm.GLMModel.GLMWeightsFun
linkInv(double) - Method in class hex.glm.GLMModel.GLMParameters
linkInv(double) - Method in class hex.glm.GLMModel.GLMWeightsFun
linkInvDeriv(double) - Method in class hex.glm.GLMModel.GLMParameters
lmulCatBlock(double[], int) - Method in class hex.glrm.GLRM.Archetypes
lmulNumCol(double[], int) - Method in class hex.glrm.GLRM.Archetypes
loading_name - Variable in class hex.schemas.GLRMV3.GLRMParametersV3
localModelInfoKey(H2ONode) - Method in class hex.deeplearning.DeepLearningModelInfo
loss - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3: The loss (error) function to be minimized by the model.
loss - Variable in class hex.schemas.GLRMV3.GLRMParametersV3
loss_by_col - Variable in class hex.schemas.GLRMV3.GLRMParametersV3
loss_by_col_idx - Variable in class hex.schemas.GLRMV3.GLRMParametersV3
lre_min - Variable in class hex.coxph.CoxPHModel.CoxPHParameters

M

make(String, int, byte, double, double, long, SharedTreeModel.SharedTreeParameters, Key) - Static method in class hex.tree.DHistogram
make_model(int, MakeGLMModelV3) - Method in class hex.api.MakeGLMModelHandler
makeDecided(DTree.UndecidedNode, DHistogram[]) - Method in class hex.tree.SharedTree
MakeGLMModelHandler - Class in hex.api: Created by tomasnykodym on 3/25/15.
MakeGLMModelHandler() - Constructor for class hex.api.MakeGLMModelHandler
MakeGLMModelV3 - Class in hex.schemas: End point to update a model.
MakeGLMModelV3() - Constructor for class hex.schemas.MakeGLMModelV3
makeMetricBuilder(String[]) - Method in class hex.aggregator.AggregatorModel
makeMetricBuilder(String[]) - Method in class hex.coxph.CoxPHModel
makeMetricBuilder(String[]) - Method in class hex.deeplearning.DeepLearningModel
makeMetricBuilder(String[]) - Method in class hex.deepwater.DeepWaterModel
makeMetricBuilder(String[]) - Method in class hex.example.ExampleModel
makeMetricBuilder(String[]) - Method in class hex.glm.GLMModel
makeMetricBuilder(String[]) - Method in class hex.glrm.GLRMModel
makeMetricBuilder(String[]) - Method in class hex.grep.GrepModel
makeMetricBuilder(String[]) - Method in class hex.kmeans.KMeansModel
makeMetricBuilder(String[]) - Method in class hex.naivebayes.NaiveBayesModel
makeMetricBuilder(String[]) - Method in class hex.pca.PCAModel
makeMetricBuilder(String[]) - Method in class hex.StackedEnsembleModel
makeMetricBuilder(String[]) - Method in class hex.svd.SVDModel
makeMetricBuilder(String[]) - Method in class hex.tree.SharedTreeModel
makeMetricBuilder(String[]) - Method in class hex.word2vec.Word2VecModel
makeModel(Key<M>, P) - Method in class hex.tree.SharedTree.Driver
makeModelMetrics(Model, Frame, Frame, Frame) - Method in class hex.aggregator.ModelMetricsAggregator.AggregatorModelMetrics
makeModelMetrics(Model, Frame, Frame, Frame) - Method in class hex.glm.GLMMetricBuilder
makeModelMetrics(Model, Frame, Frame, Frame) - Method in class hex.glrm.ModelMetricsGLRM.GlrmModelMetricsBuilder
makeModelMetrics(Model, Frame, Frame, Frame) - Method in class hex.pca.ModelMetricsPCA.PCAModelMetrics
makeModelMetrics(Model, Frame, Frame, Frame) - Method in class hex.svd.SVDModel.ModelMetricsSVD.SVDModelMetrics
makeNeuronsForTesting(DeepLearningModelInfo) - Static method in class hex.deeplearning.DeepLearningTask
makeNeuronsForTraining(DeepLearningModelInfo) - Static method in class hex.deeplearning.DeepLearningTask
makeScoringNames() - Method in class hex.glm.GLMModel
makeTreeKey(int, int) - Static method in class hex.tree.CompressedTree
makeUndecidedNode(DHistogram[]) - Method in class hex.tree.DTree.DecidedNode
map(Chunk[], NewChunk[]) - Method in class hex.deepwater.DeepWaterTask
map(Chunk[]) - Method in class hex.FrameTask.ExtractDenseRow
map(Chunk[], NewChunk[]) - Method in class hex.FrameTask: Extracts the values, applies regularization to numerics, adds appropriate offsets to categoricals, and adapts response according to the CaseMode/CaseValue if set.
map(Chunk[]) - Method in class hex.FrameTask2
map(Chunk[], NewChunk[]) - Method in class hex.glm.GLMScore
map(Chunk[]) - Method in class hex.glm.GLMTask.GLMCoordinateDescentTaskSeqIntercept
map(Chunk[]) - Method in class hex.glm.GLMTask.GLMCoordinateDescentTaskSeqNaive
map(Chunk[]) - Method in class hex.glm.GLMTask.GLMGenerateWeightsTask
map(Chunk[]) - Method in class hex.glm.GLMTask.GLMMultinomialUpdate
map(Chunk[]) - Method in class hex.glm.GLMTask.YMUTask
map(Chunk[]) - Method in class hex.gram.Gram.OuterGramTask
map(Chunk[]) - Method in class hex.tree.drf.TreeMeasuresCollector
map(Chunk, Chunk) - Method in class hex.tree.drf.TreeMeasuresCollector.ShuffleTask
map(Chunk[]) - Method in class hex.tree.gbm.GBM.DiffMinusMedianDiff
map(Chunk[]) - Method in class hex.tree.ReconstructTreeState
map(Chunk, Chunk) - Method in class hex.tree.Sample
map(Chunk[]) - Method in class hex.tree.Score
map(Chunk[]) - Method in class hex.tree.ScoreBuildHistogram
map(Chunk[]) - Method in class hex.tree.ScoreBuildHistogram2
map(Chunk[]) - Method in class hex.util.LinearAlgebraUtils.BMulInPlaceTask
map(Chunk[]) - Method in class hex.util.LinearAlgebraUtils.ForwardSolve
map(Chunk[]) - Method in class hex.util.LinearAlgebraUtils.ForwardSolveInPlace
map(Chunk[]) - Method in class hex.util.LinearAlgebraUtils.SMulTask
map(Chunk) - Method in class hex.word2vec.WordCountTask
map(Chunk[]) - Method in class hex.word2vec.WordVectorConverter
map(Chunk) - Method in class hex.word2vec.WordVectorTrainer
mapNames(String[]) - Method in class hex.DataInfo
matches - Variable in class hex.schemas.GrepModelV3.GrepModelOutputV3
max_abs_leafnode_pred - Variable in class hex.schemas.GBMV3.GBMParametersV3
max_active_predictors - Variable in class hex.schemas.GLMV3.GLMParametersV3
max_after_balance_size - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3: When classes are balanced, limit the resulting dataset size to the specified multiple of the original dataset size.
max_after_balance_size - Variable in class hex.schemas.DeepWaterV3.DeepWaterParametersV3: When classes are balanced, limit the resulting dataset size to the specified multiple of the original dataset size.
max_after_balance_size - Variable in class hex.schemas.GLMV3.GLMParametersV3: When classes are balanced, limit the resulting dataset size to the specified multiple of the original dataset size.
max_after_balance_size - Variable in class hex.schemas.NaiveBayesV3.NaiveBayesParametersV3: When classes are balanced, limit the resulting dataset size to the specified multiple of the original dataset size.
max_after_balance_size - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3: When classes are balanced, limit the resulting dataset size to the specified multiple of the original dataset size.
max_categorical_features - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
max_confusion_matrix_size - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3: For classification models, the maximum size (in terms of classes) of the confusion matrix for it to be printed.
max_confusion_matrix_size - Variable in class hex.schemas.DeepWaterV3.DeepWaterParametersV3: For classification models, the maximum size (in terms of classes) of the confusion matrix for it to be printed.
max_confusion_matrix_size - Variable in class hex.schemas.GLMV3.GLMParametersV3: For classification models, the maximum size (in terms of classes) of the confusion matrix for it to be printed.
max_confusion_matrix_size - Variable in class hex.schemas.NaiveBayesV3.NaiveBayesParametersV3: For classification models, the maximum size (in terms of classes) of the confusion matrix for it to be printed.
max_confusion_matrix_size - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3: For classification models, the maximum size (in terms of classes) of the confusion matrix for it to be printed.
max_depth - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3
max_depth - Variable in class hex.schemas.TreeStatsV3
max_hit_ratio_k - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3: The maximum number (top K) of predictions to use for hit ratio computation (for multi-class only, 0 to disable)
max_hit_ratio_k - Variable in class hex.schemas.DeepWaterV3.DeepWaterParametersV3: The maximum number (top K) of predictions to use for hit ratio computation (for multi-class only, 0 to disable)
max_hit_ratio_k - Variable in class hex.schemas.GLMV3.GLMParametersV3: The maximum number (top K) of predictions to use for hit ratio computation (for multi-class only, 0 to disable)
max_hit_ratio_k - Variable in class hex.schemas.NaiveBayesV3.NaiveBayesParametersV3: The maximum number (top K) of predictions to use for hit ratio computation (for multi-class only, 0 to disable)
max_hit_ratio_k - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3: The maximum number (top K) of predictions to use for hit ratio computation (for multi-class only, 0 to disable)
max_iterations - Variable in class hex.schemas.AggregatorV99.AggregatorParametersV99
max_iterations - Variable in class hex.schemas.ExampleV3.ExampleParametersV3
max_iterations - Variable in class hex.schemas.GLMV3.GLMParametersV3
max_iterations - Variable in class hex.schemas.GLRMV3.GLRMParametersV3
max_iterations - Variable in class hex.schemas.KMeansV3.KMeansParametersV3
max_iterations - Variable in class hex.schemas.PCAV3.PCAParametersV3
max_iterations - Variable in class hex.schemas.SVDV99.SVDParametersV99
max_leaves - Variable in class hex.schemas.TreeStatsV3
MAX_NTREES - Static variable in class hex.tree.SharedTree
max_updates - Variable in class hex.schemas.GLRMV3.GLRMParametersV3
max_w2 - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3: A maximum on the sum of the squared incoming weights into any one neuron.
maxIter() - Method in class hex.optimization.L_BFGS
maxs - Variable in class hex.schemas.ExampleModelV3.ExampleModelOutputV3
mean_a - Variable in class hex.deeplearning.DeepLearningModelInfo
mean_depth - Variable in class hex.schemas.TreeStatsV3
mean_image_file - Variable in class hex.schemas.DeepWaterV3.DeepWaterParametersV3
mean_leaves - Variable in class hex.schemas.TreeStatsV3
meanLoss(DataInfo.Row[]) - Method in class hex.deeplearning.DeepLearningModel: Compute the loss function
messages - Variable in class hex.optimization.OptimizationUtils.MoreThuente
mid(int, float, int) - Method in class hex.tree.TreeVisitor
min_depth - Variable in class hex.schemas.TreeStatsV3
min_leaves - Variable in class hex.schemas.TreeStatsV3
min_prob - Variable in class hex.schemas.NaiveBayesV3.NaiveBayesParametersV3
min_rows - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3
min_sdev - Variable in class hex.schemas.NaiveBayesV3.NaiveBayesParametersV3
min_split_improvement - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3
min_step_size - Variable in class hex.schemas.GLRMV3.GLRMParametersV3
min_word_freq - Variable in class hex.schemas.Word2VecV3.Word2VecParametersV3
mini_batch_size - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
mini_batch_size - Variable in class hex.schemas.DeepWaterV3.DeepWaterParametersV3
MISSING_RESPONSE - Static variable in class hex.tree.ScoreBuildHistogram: Marker for rows without a response
missing_values_handling - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
missing_values_handling - Variable in class hex.schemas.GLMV3.GLMParametersV3
missingColumnsType() - Method in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
model - Variable in class hex.schemas.GLMRegularizationPathV3
model - Variable in class hex.schemas.MakeGLMModelV3
model - Variable in class hex.schemas.Word2VecSynonymsV3
model - Variable in class hex.schemas.Word2VecTransformV3
model_info() - Method in class hex.deeplearning.DeepLearningModel
model_info() - Method in class hex.deeplearning.DeepLearningTask: Accessor to the object containing the (final) state of the Deep Learning model Should only be queried after calling this.doAll(Frame training)
model_info() - Method in class hex.deeplearning.DeepLearningTask2: Returns the aggregated DeepLearning model that was trained by all nodes (over all the training data)
model_info() - Method in class hex.deepwater.DeepWaterModel
model_info() - Method in class hex.deepwater.DeepWaterTask: Accessor to the object containing the (final) state of the Deep Learning model Should only be queried after calling this.doAll(Frame training)
model_info_key - Variable in class hex.deeplearning.DeepLearningModel
modelCategory - Variable in class hex.StackedEnsembleModel
ModelMetricsAggregator - Class in hex.aggregator
ModelMetricsAggregator(Model, Frame) - Constructor for class hex.aggregator.ModelMetricsAggregator
ModelMetricsAggregator.AggregatorModelMetrics - Class in hex.aggregator
ModelMetricsAggregator.AggregatorModelMetrics(int) - Constructor for class hex.aggregator.ModelMetricsAggregator.AggregatorModelMetrics
ModelMetricsGLRM - Class in hex.glrm
ModelMetricsGLRM(Model, Frame, double, double) - Constructor for class hex.glrm.ModelMetricsGLRM
ModelMetricsGLRM(Model, Frame, double, double, long, long) - Constructor for class hex.glrm.ModelMetricsGLRM
ModelMetricsGLRM.GlrmModelMetricsBuilder - Class in hex.glrm
ModelMetricsGLRM.GlrmModelMetricsBuilder(int, int[]) - Constructor for class hex.glrm.ModelMetricsGLRM.GlrmModelMetricsBuilder
ModelMetricsGLRM.GlrmModelMetricsBuilder(int, int[], boolean) - Constructor for class hex.glrm.ModelMetricsGLRM.GlrmModelMetricsBuilder
ModelMetricsGLRMV99 - Class in water.api
ModelMetricsGLRMV99() - Constructor for class water.api.ModelMetricsGLRMV99
ModelMetricsPCA - Class in hex.pca
ModelMetricsPCA(Model, Frame) - Constructor for class hex.pca.ModelMetricsPCA
ModelMetricsPCA.PCAModelMetrics - Class in hex.pca
ModelMetricsPCA.PCAModelMetrics(int) - Constructor for class hex.pca.ModelMetricsPCA.PCAModelMetrics
ModelMetricsPCAV3 - Class in water.api
ModelMetricsPCAV3() - Constructor for class water.api.ModelMetricsPCAV3
ModelMetricsSVDV99 - Class in water.api
ModelMetricsSVDV99() - Constructor for class water.api.ModelMetricsSVDV99
mojoVersion() - Method in class hex.deepwater.DeepwaterMojoWriter
mojoVersion() - Method in class hex.glm.GLMMojoWriter
mojoVersion() - Method in class hex.glrm.GlrmMojoWriter
mojoVersion() - Method in class hex.kmeans.KMeansMojoWriter
mojoVersion() - Method in class hex.tree.drf.DrfMojoWriter
mojoVersion() - Method in class hex.tree.gbm.GbmMojoWriter
mojoVersion() - Method in class hex.word2vec.Word2VecMojoWriter
momentum() - Method in class hex.deeplearning.Neurons
momentum(double) - Method in class hex.deeplearning.Neurons: The momentum - real number in [0, 1) Can be a linear ramp from momentum_start to momentum_stable, over momentum_ramp training samples
momentum(double) - Method in class hex.deepwater.DeepWaterParameters
momentum_ramp - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3: The momentum_ramp parameter controls the amount of learning for which momentum increases (assuming momentum_stable is larger than momentum_start).
momentum_ramp - Variable in class hex.schemas.DeepWaterV3.DeepWaterParametersV3: The momentum_ramp parameter controls the amount of learning for which momentum increases (assuming momentum_stable is larger than momentum_start).
momentum_stable - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3: The momentum_stable parameter controls the final momentum value reached after momentum_ramp training samples.
momentum_stable - Variable in class hex.schemas.DeepWaterV3.DeepWaterParametersV3: The momentum_stable parameter controls the final momentum value reached after momentum_ramp training samples.
momentum_start - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3: The momentum_start parameter controls the amount of momentum at the beginning of training.
momentum_start - Variable in class hex.schemas.DeepWaterV3.DeepWaterParametersV3: The momentum_start parameter controls the amount of momentum at the beginning of training.
mtries - Variable in class hex.schemas.DRFV3.DRFParametersV3
mtrxMul(double[][], double[]) - Method in class hex.DataInfo.Row
mu - Variable in class hex.glm.GLMModel.GLMWeights
mul(double) - Method in class hex.gram.Gram
mul(double[]) - Method in class hex.gram.Gram
mul(double[], double[]) - Method in class hex.gram.Gram
mult(double) - Method in class hex.deeplearning.DeepLearningModelInfo: Multiply all weights/biases by a real-valued number
mult(double) - Method in class hex.deepwater.DeepWaterModelInfo
multi_loss - Variable in class hex.schemas.GLRMV3.GLRMParametersV3
MurmurHash - Class in hex.deeplearning: This is a very fast, non-cryptographic hash suitable for general hash-based lookup.
MurmurHash() - Constructor for class hex.deeplearning.MurmurHash

N

n - Variable in class hex.coxph.CoxPH.CoxPHTask
NaiveBayes - Class in hex.naivebayes: Naive Bayes This is an algorithm for computing the conditional a-posterior probabilities of a categorical response from independent predictors using Bayes rule.
NaiveBayes(NaiveBayesModel.NaiveBayesParameters) - Constructor for class hex.naivebayes.NaiveBayes
NaiveBayes(boolean) - Constructor for class hex.naivebayes.NaiveBayes
NaiveBayesModel - Class in hex.naivebayes
NaiveBayesModel(Key, NaiveBayesModel.NaiveBayesParameters, NaiveBayesModel.NaiveBayesOutput) - Constructor for class hex.naivebayes.NaiveBayesModel
NaiveBayesModel.NaiveBayesOutput - Class in hex.naivebayes
NaiveBayesModel.NaiveBayesOutput(NaiveBayes) - Constructor for class hex.naivebayes.NaiveBayesModel.NaiveBayesOutput
NaiveBayesModel.NaiveBayesParameters - Class in hex.naivebayes
NaiveBayesModel.NaiveBayesParameters() - Constructor for class hex.naivebayes.NaiveBayesModel.NaiveBayesParameters
NaiveBayesModelV3 - Class in hex.schemas
NaiveBayesModelV3() - Constructor for class hex.schemas.NaiveBayesModelV3
NaiveBayesModelV3.NaiveBayesModelOutputV3 - Class in hex.schemas
NaiveBayesModelV3.NaiveBayesModelOutputV3() - Constructor for class hex.schemas.NaiveBayesModelV3.NaiveBayesModelOutputV3
NaiveBayesV3 - Class in hex.schemas
NaiveBayesV3() - Constructor for class hex.schemas.NaiveBayesV3
NaiveBayesV3.NaiveBayesParametersV3 - Class in hex.schemas
NaiveBayesV3.NaiveBayesParametersV3() - Constructor for class hex.schemas.NaiveBayesV3.NaiveBayesParametersV3
names() - Method in class hex.glm.GLMModel
names - Variable in class hex.schemas.MakeGLMModelV3
nargs() - Method in class water.rapids.prims.word2vec.AstWord2VecToFrame
nBins - Variable in class hex.DataInfo.Row
nbins - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3
nbins() - Method in class hex.tree.DHistogram
nbins_cats - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3
nbins_top_level - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3
nclasses() - Method in class hex.glm.GLM
nclasses() - Method in class hex.glm.GLMModel.GLMOutput
nesterov_accelerated_gradient - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3: The Nesterov accelerated gradient descent method is a modification to traditional gradient descent for convex functions.
network - Variable in class hex.schemas.DeepWaterV3.DeepWaterParametersV3
network_definition_file - Variable in class hex.schemas.DeepWaterV3.DeepWaterParametersV3
network_parameters_file - Variable in class hex.schemas.DeepWaterV3.DeepWaterParametersV3
Neurons - Class in hex.deeplearning: This class implements the concept of a Neuron layer in a Neural Network During training, every MRTask F/J thread is expected to create these neurons for every map call (Cheap to make).
Neurons.ExpRectifier - Class in hex.deeplearning
Neurons.ExpRectifier(int) - Constructor for class hex.deeplearning.Neurons.ExpRectifier
Neurons.ExpRectifierDropout - Class in hex.deeplearning: Exponential Rectifier with dropout
Neurons.ExpRectifierDropout(int) - Constructor for class hex.deeplearning.Neurons.ExpRectifierDropout
Neurons.Input - Class in hex.deeplearning: Input layer of the Neural Network This layer is different from other layers as it has no incoming weights, but instead gets its activation values from the training points.
Neurons.Linear - Class in hex.deeplearning: Output neurons for regression - Linear units
Neurons.Linear() - Constructor for class hex.deeplearning.Neurons.Linear
Neurons.Maxout - Class in hex.deeplearning: Maxout neurons (picks the max out of the k activation_j = sum(A_ij*x_i) + b_j) Requires k times the model parameters (weights/biases) as a "normal" neuron
Neurons.Maxout(DeepLearningModel.DeepLearningParameters, short, int) - Constructor for class hex.deeplearning.Neurons.Maxout
Neurons.MaxoutDropout - Class in hex.deeplearning: Maxout neurons with dropout
Neurons.MaxoutDropout(DeepLearningModel.DeepLearningParameters, short, 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.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
newDenseRow() - Method in class hex.DataInfo
newDenseRow(double[], long) - Method in class hex.DataInfo
nextLevelHistos(DHistogram[], int, double, SharedTreeModel.SharedTreeParameters) - Method in class hex.tree.DTree.Split: Prepare children histograms, one per column.
nextNumericIdx(int) - Method in class hex.DataInfo: Get the next expanded number-column index.
nfeatures() - Method in class hex.aggregator.AggregatorModel.AggregatorOutput
nfeatures() - Method in class hex.glrm.GLRM.Archetypes
nfeatures() - Method in class hex.glrm.GLRMModel.GLRMOutput: Override because base class implements ncols-1 for features with the last column as a response variable; for GLRM all the columns are features.
nfeatures() - Method in class hex.pca.PCAModel.PCAOutput: Override because base class implements ncols-1 for features with the last column as a response variable; for PCA all the columns are features.
nfeval() - Method in interface hex.optimization.OptimizationUtils.LineSearchSolver
nfeval() - Method in class hex.optimization.OptimizationUtils.MoreThuente
nfeval() - Method in class hex.optimization.OptimizationUtils.SimpleBacktrackingLS
nfolds - Variable in class hex.StackedEnsembleModel
nid() - Method in class hex.tree.DTree.Node
nid2Oob(int) - Static method in class hex.tree.ScoreBuildHistogram
nids0Index - Variable in class hex.tree.SharedTree.FrameMap
nlambdas - Variable in class hex.schemas.GLMV3.GLMParametersV3
nModelsInParallel() - Method in class hex.deeplearning.DeepLearning
nModelsInParallel() - Method in class hex.deepwater.DeepWater
nModelsInParallel() - Method in class hex.tree.gbm.GBM
nNums - Variable in class hex.DataInfo.Row
NO_PARENT - Static variable in class hex.tree.DTree
nobs() - Method in class hex.glm.GLMTask.YMUTask
node(int) - Method in class hex.tree.DTree
non_negative - Variable in class hex.schemas.GLMV3.GLMParametersV3
norm_model - Variable in class hex.schemas.Word2VecV3.Word2VecParametersV3
nOutpus - Variable in class hex.DataInfo.Row
npredictors() - Method in class hex.tree.drf.TreeMeasuresCollector.TreeMeasures: Returns number of voting predictors
nrows() - Method in class hex.tree.drf.TreeMeasuresCollector.TreeMeasures: Returns number of rows which were used during voting per individual tree.
ntrees - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3
ntrees() - Method in class hex.tree.DTreeScorer
nullDOF() - Method in class hex.glm.GLMMetricBuilder
numCats() - Method in class hex.DataInfo
numcnt - Variable in class water.api.ModelMetricsGLRMV99
numColsExp(Frame, boolean) - Static method in class hex.util.LinearAlgebraUtils: Number of columns with categoricals expanded.
numerr - Variable in class water.api.ModelMetricsGLRMV99
numIds - Variable in class hex.DataInfo.Row
numNums() - Method in class hex.DataInfo
numStart() - Method in class hex.DataInfo
numVals - Variable in class hex.DataInfo.Row
nv - Variable in class hex.schemas.SVDV99.SVDParametersV99

O

obj_reg - Variable in class hex.schemas.GLMV3.GLMParametersV3
objective() - Method in class hex.glm.ComputationState
objective(double[], double) - Method in class hex.glm.ComputationState
objective - Variable in class hex.schemas.GLRMModelV3.GLRMModelOutputV3
objective - Variable in class hex.schemas.PCAModelV3.PCAModelOutputV3
objective_epsilon - Variable in class hex.schemas.GLMV3.GLMParametersV3
offset - Variable in class hex.DataInfo.Row
offset_columns - Variable in class hex.coxph.CoxPHModel.CoxPHParameters
offsetChunkId() - Method in class hex.DataInfo
offsetIndex - Variable in class hex.tree.SharedTree.FrameMap
offsets - Variable in class hex.schemas.GrepModelV3.GrepModelOutputV3
oneHot(Frame, String[], boolean, boolean, boolean, boolean) - Static method in class hex.api.MakeGLMModelHandler
onExceptionalCompletion(Throwable, CountedCompleter) - Method in class hex.glm.GLM.GLMDriver
oob2Nid(int) - Static method in class hex.tree.ScoreBuildHistogram
oobtIndex - Variable in class hex.tree.SharedTree.FrameMap
OptimizationUtils - Class in hex.optimization: Created by tomasnykodym on 9/29/15.
OptimizationUtils() - Constructor for class hex.optimization.OptimizationUtils
OptimizationUtils.GradientInfo - Class in hex.optimization
OptimizationUtils.GradientInfo(double, double[]) - Constructor for class hex.optimization.OptimizationUtils.GradientInfo
OptimizationUtils.GradientSolver - Interface in hex.optimization: Provides ginfo computation and line search evaluation specific to given problem.
OptimizationUtils.LineSearchSolver - Interface in hex.optimization
OptimizationUtils.MoreThuente - Class in hex.optimization
OptimizationUtils.MoreThuente(OptimizationUtils.GradientSolver, double[]) - Constructor for class hex.optimization.OptimizationUtils.MoreThuente
OptimizationUtils.MoreThuente(OptimizationUtils.GradientSolver, double[], OptimizationUtils.GradientInfo) - Constructor for class hex.optimization.OptimizationUtils.MoreThuente
OptimizationUtils.MoreThuente(OptimizationUtils.GradientSolver, double[], OptimizationUtils.GradientInfo, double, double, double) - Constructor for class hex.optimization.OptimizationUtils.MoreThuente
OptimizationUtils.SimpleBacktrackingLS - Class in hex.optimization
OptimizationUtils.SimpleBacktrackingLS(OptimizationUtils.GradientSolver, double[], double) - Constructor for class hex.optimization.OptimizationUtils.SimpleBacktrackingLS
OptimizationUtils.SimpleBacktrackingLS(OptimizationUtils.GradientSolver, double[], double, OptimizationUtils.GradientInfo) - Constructor for class hex.optimization.OptimizationUtils.SimpleBacktrackingLS
OUT_OF_BAG - Static variable in class hex.tree.ScoreBuildHistogram: Marker for sampled out rows
output_frame - Variable in class hex.schemas.AggregatorModelV99.AggregatorModelOutputV99
outputChunkId() - Method in class hex.DataInfo
outputChunkId(int) - Method in class hex.DataInfo
overwrite_with_best_model - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3: If enabled, store the best model under the destination key of this model at the end of training.
overwrite_with_best_model - Variable in class hex.schemas.DeepWaterV3.DeepWaterParametersV3: If enabled, store the best model under the destination key of this model at the end of training.
own_fields - Static variable in class hex.schemas.CoxPHV3.CoxPHParametersV3
own_fields - Static variable in class hex.schemas.ExampleV3.ExampleParametersV3
own_fields - Static variable in class hex.schemas.GrepV3.GrepParametersV3

P

parameters - Variable in class hex.deeplearning.DeepLearningModelInfo
parameters - Variable in class hex.deepwater.DeepWaterModelInfo
params - Variable in class hex.deeplearning.Neurons: Parameters (deep-cloned() from the user input, can be modified here, e.g.
PCA - Class in hex.pca: Principal Components Analysis It computes the principal components from the singular value decomposition using the power method.
PCA(PCAModel.PCAParameters) - Constructor for class hex.pca.PCA
PCA(boolean) - Constructor for class hex.pca.PCA
pca_method - Variable in class hex.schemas.AggregatorV99.AggregatorParametersV99
pca_method - Variable in class hex.schemas.PCAV3.PCAParametersV3
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
PCAModel.PCAParameters.Method - Enum in hex.pca
PCAModelV3 - Class in hex.schemas
PCAModelV3() - Constructor for class hex.schemas.PCAModelV3
PCAModelV3.PCAModelOutputV3 - Class in hex.schemas
PCAModelV3.PCAModelOutputV3() - Constructor for class hex.schemas.PCAModelV3.PCAModelOutputV3
PCAV3 - Class in hex.schemas
PCAV3() - Constructor for class hex.schemas.PCAV3
PCAV3.PCAParametersV3 - Class in hex.schemas
PCAV3.PCAParametersV3() - Constructor for class hex.schemas.PCAV3.PCAParametersV3
pcond - Variable in class hex.schemas.NaiveBayesModelV3.NaiveBayesModelOutputV3
period - Variable in class hex.schemas.GLRMV3.GLRMParametersV3
perRow(double[], float[], Model) - Method in class hex.aggregator.ModelMetricsAggregator.AggregatorModelMetrics
perRow(double[], float[], Model) - Method in class hex.glm.GLMMetricBuilder
perRow(double[], float[], double, double, Model) - Method in class hex.glm.GLMMetricBuilder
perRow(double[], float[], Model) - Method in class hex.glrm.ModelMetricsGLRM.GlrmModelMetricsBuilder
perRow(double[], float[], Model) - Method in class hex.pca.ModelMetricsPCA.PCAModelMetrics
perRow(double[], float[], Model) - Method in class hex.svd.SVDModel.ModelMetricsSVD.SVDModelMetrics
pickBestModel() - Method in class hex.glm.GLMModel.GLMOutput
pid() - Method in class hex.tree.DTree.Node
post(int, float, int) - Method in class hex.tree.TreeVisitor
postGlobal() - Method in class hex.coxph.CoxPH.CoxPHTask
postGlobal() - Method in class hex.deeplearning.DeepLearningTask: After all reduces are done, the driver node calls this method to clean up This is only needed if we're not inside a DeepLearningTask2 (which will do the reduction between replicated data workers).
postGlobal() - Method in class hex.deeplearning.DeepLearningTask2: Finish up the work after all nodes have reduced their models via the above reduce() method.
postGlobal() - Method in class hex.deepwater.DeepWaterTask: After all reduces are done, the driver node calls this method to clean up This is only needed if we're not inside a DeepWaterTask2 (which will do the reduction between replicated data workers).
postGlobal() - Method in class hex.glm.GLMScore
postGlobal() - Method in class hex.glm.GLMTask.LSTask
postGlobal() - Method in class hex.glm.GLMTask.YMUTask
postGlobal() - Method in class hex.tree.ScoreBuildHistogram2
postProcessPredictions(Frame) - Method in class hex.tree.SharedTreeModel
pre(int, float, IcedBitSet, int, int) - Method in class hex.tree.TreeVisitor
pre_split_se() - Method in class hex.tree.DTree.Split
pre_trained - Variable in class hex.schemas.Word2VecV3.Word2VecParametersV3
pred(int) - Method in class hex.tree.DTree.DecidedNode
pred() - Method in class hex.tree.DTree.LeafNode
pred_noise_bandwidth - Variable in class hex.schemas.GBMV3.GBMParametersV3
predictorMeans() - Method in class hex.glm.GLMTask.YMUTask
predictors_bad - Variable in class hex.DataInfo.Row
predictorSDs() - Method in class hex.glm.GLMTask.YMUTask
predictScoreImpl(Frame, Frame, String, Job, boolean) - Method in class hex.aggregator.AggregatorModel
predictScoreImpl(Frame, Frame, String, Job, boolean) - Method in class hex.deeplearning.DeepLearningModel: Make either a prediction or a reconstruction.
predictScoreImpl(Frame, Frame, String, Job, boolean) - Method in class hex.deepwater.DeepWaterModel
predictScoreImpl(Frame, Frame, String, Job, boolean) - Method in class hex.glm.GLMModel: Score an already adapted frame.
predictScoreImpl(Frame, Frame, String, Job, boolean) - Method in class hex.glrm.GLRMModel
predictScoreImpl(Frame, Frame, String, Job, boolean) - Method in class hex.kmeans.KMeansModel
predictScoreImpl(Frame, Frame, String, Job, boolean) - Method in class hex.pca.PCAModel
predictScoreImpl(Frame, Frame, String, Job, boolean) - Method in class hex.StackedEnsembleModel: For StackedEnsemble we call score on all the base_models and then combine the results with the metalearner to create the final predictions frame.
predictScoreImpl(Frame, Frame, String, Job, boolean) - Method in class hex.svd.SVDModel
pretrained_autoencoder - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
printGenerateTrees(DTree[]) - Static method in class hex.tree.SharedTree
prior - Variable in class hex.schemas.GLMV3.GLMParametersV3
problem_type - Variable in class hex.schemas.DeepWaterV3.DeepWaterParametersV3: The activation function (non-linearity) to be used by the neurons in the hidden layers.
processMiniBatch(long, double[], double[], int) - Method in class hex.deeplearning.DeepLearningTask: Apply the gradient to update the weights
processMiniBatch(long, double[], double[], int) - Method in class hex.FrameTask: Mini-Batch update of model parameters
processRow(long, DataInfo.Row) - Method in class hex.coxph.CoxPH.CoxPHTask
processRow(long, DataInfo.Row, int) - Method in class hex.deeplearning.DeepLearningTask: Process one training row at a time (online learning)
processRow(long, DataInfo.Row) - Method in class hex.FrameTask: Method to process one row of the data.
processRow(long, DataInfo.Row, NewChunk[]) - Method in class hex.FrameTask
processRow(long, DataInfo.Row, int) - Method in class hex.FrameTask
processRow(DataInfo.Row) - Method in class hex.FrameTask2
processRow(DataInfo.Row) - Method in class hex.glm.GLMTask.ComputeSETsk
processRow(DataInfo.Row) - Method in class hex.glm.GLMTask.GLMIterationTask
processRow(DataInfo.Row) - Method in class hex.glm.GLMTask.GLMIterationTaskMultinomial
processRow(DataInfo.Row) - Method in class hex.glm.GLMTask.GLMMultinomialUpdate
processRow(DataInfo.Row) - Method in class hex.glm.GLMTask.GLMMultinomialWLSTask
processRow(DataInfo.Row) - Method in class hex.glm.GLMTask.GLMWLSTask
processRow(DataInfo.Row) - Method in class hex.glm.GLMTask.LSTask
processRow(DataInfo.Row) - Method in class hex.gram.Gram.GramTask
processRow(long, DataInfo.Row, NewChunk[]) - Method in class hex.util.LinearAlgebraUtils.BMulTask
progress(double[], OptimizationUtils.GradientInfo) - Method in class hex.glm.GLM.GLMDriver
progress(double[], double) - Method in class hex.glm.GLM.GLMDriver
progress(double[], OptimizationUtils.GradientInfo) - Method in interface hex.optimization.L_BFGS.ProgressMonitor
progressUnits() - Method in class hex.aggregator.AggregatorModel.AggregatorParameters
progressUnits() - Method in class hex.coxph.CoxPHModel.CoxPHParameters
progressUnits() - Method in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
progressUnits() - Method in class hex.deepwater.DeepWaterParameters
progressUnits() - Method in class hex.example.ExampleModel.ExampleParameters
progressUnits() - Method in class hex.glm.GLMModel.GLMParameters
progressUnits() - Method in class hex.glrm.GLRMModel.GLRMParameters
progressUnits() - Method in class hex.grep.GrepModel.GrepParameters
progressUnits() - Method in class hex.kmeans.KMeansModel.KMeansParameters
progressUnits() - Method in class hex.naivebayes.NaiveBayesModel.NaiveBayesParameters
progressUnits() - Method in class hex.pca.PCAModel.PCAParameters
progressUnits() - Method in class hex.StackedEnsembleModel.StackedEnsembleParameters
progressUnits() - Method in class hex.svd.SVDModel.SVDParameters
progressUnits() - Method in class hex.tree.SharedTreeModel.SharedTreeParameters
progressUnits() - Method in class hex.word2vec.Word2VecModel.Word2VecParameters
proximal_gradient(double[], double, double[], double[], double[]) - Static method in class hex.glm.GLM.ProximalGradientSolver
pValues() - Method in class hex.glm.GLMModel.GLMOutput

Q

qrCholesky(ArrayList<Integer>, boolean) - Method in class hex.gram.Gram: Compute Cholesky decompostion by computing partial QR decomposition (R == LU).
quiet_mode - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3: Enable quiet mode for less output to standard output.
quiet_mode - Variable in class hex.schemas.DeepWaterV3.DeepWaterParametersV3: Enable quiet mode for less output to standard output.

R

r2_stopping - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3
randomlySparsifyActivation(Storage.Vector, long) - Method in class hex.deeplearning.Dropout
rank() - Method in class hex.glm.GLMModel.GLMOutput
rank() - Method in class hex.glm.GLMModel.Submodel
rank() - Method in class hex.glrm.GLRM.Archetypes
rate(double) - Method in class hex.deeplearning.Neurons: The learning rate
rate - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3: When adaptive learning rate is disabled, the magnitude of the weight updates are determined by the user specified learning rate (potentially annealed), and are a function of the difference between the predicted value and the target value.
rate_annealing - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3: Learning rate annealing reduces the learning rate to "freeze" into local minima in the optimization landscape.
rate_decay - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3: The learning rate decay parameter controls the change of learning rate across layers.
raw() - Method in class hex.deeplearning.Storage.DenseColMatrix
raw() - Method in class hex.deeplearning.Storage.DenseRowMatrix
raw() - Method in class hex.deeplearning.Storage.DenseVector
raw() - Method in interface hex.deeplearning.Storage.Matrix
raw() - Method in class hex.deeplearning.Storage.SparseRowMatrix
raw() - Method in interface hex.deeplearning.Storage.Tensor
raw() - Method in interface hex.deeplearning.Storage.Vector
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
readAll_impl(AutoBuffer, Futures) - Method in class hex.glrm.GLRMModel
readAll_impl(AutoBuffer, Futures) - Method in class hex.StackedEnsembleModel: Read in models (base + metalearner)
readAll_impl(AutoBuffer, Futures) - Method in class hex.svd.SVDModel
readAll_impl(AutoBuffer, Futures) - Method in class hex.tree.SharedTreeModel
rebalance(Frame, boolean, String) - Method in class hex.deeplearning.DeepLearning
ReconstructTreeState - Class in hex.tree: Computing oob scores over all trees and rows and reconstructing ntree_id, oobt fields in given frame.
ReconstructTreeState(int, int, SharedTree, double, Key[][], boolean) - Constructor for class hex.tree.ReconstructTreeState
recover_svd - Variable in class hex.schemas.GLRMV3.GLRMParametersV3
reduce(CoxPH.CoxPHTask) - Method in class hex.coxph.CoxPH.CoxPHTask
reduce(DeepLearningTask) - Method in class hex.deeplearning.DeepLearningTask: Average the per-node models (for elastic averaging, already wrote them to DKV in postLocal()) This is a no-op between F/J worker threads (operate on the same weights/biases)
reduce(DeepLearningTask2) - Method in class hex.deeplearning.DeepLearningTask2: Reduce between worker nodes, with network traffic (if greater than 1 nodes) After all reduce()'s are done, postGlobal() will be called
reduce(DeepWaterTask) - Method in class hex.deepwater.DeepWaterTask: Average the per-node models (for elastic averaging, already wrote them to DKV in postLocal()) This is a no-op between F/J worker threads (operate on the same weights/biases)
reduce(FrameTask.ExtractDenseRow) - Method in class hex.FrameTask.ExtractDenseRow
reduce(GLMMetricBuilder) - Method in class hex.glm.GLMMetricBuilder
reduce(GLMScore) - Method in class hex.glm.GLMScore
reduce(GLMTask.ComputeSETsk) - Method in class hex.glm.GLMTask.ComputeSETsk
reduce(GLMTask.GLMCoordinateDescentTaskSeqIntercept) - Method in class hex.glm.GLMTask.GLMCoordinateDescentTaskSeqIntercept
reduce(GLMTask.GLMCoordinateDescentTaskSeqNaive) - Method in class hex.glm.GLMTask.GLMCoordinateDescentTaskSeqNaive
reduce(GLMTask.GLMGenerateWeightsTask) - Method in class hex.glm.GLMTask.GLMGenerateWeightsTask
reduce(GLMTask.GLMIterationTask) - Method in class hex.glm.GLMTask.GLMIterationTask
reduce(GLMTask.GLMIterationTaskMultinomial) - Method in class hex.glm.GLMTask.GLMIterationTaskMultinomial
reduce(GLMTask.LSTask) - Method in class hex.glm.GLMTask.LSTask
reduce(GLMTask.YMUTask) - Method in class hex.glm.GLMTask.YMUTask
reduce(ModelMetricsGLRM.GlrmModelMetricsBuilder) - Method in class hex.glrm.ModelMetricsGLRM.GlrmModelMetricsBuilder
reduce(Gram.GramTask) - Method in class hex.gram.Gram.GramTask
reduce(Gram.OuterGramTask) - Method in class hex.gram.Gram.OuterGramTask
reduce(TreeMeasuresCollector) - Method in class hex.tree.drf.TreeMeasuresCollector
reduce(Score) - Method in class hex.tree.Score
reduce(ScoreBuildHistogram) - Method in class hex.tree.ScoreBuildHistogram
reduce(LinearAlgebraUtils.SMulTask) - Method in class hex.util.LinearAlgebraUtils.SMulTask
reduce(WordCountTask) - Method in class hex.word2vec.WordCountTask
reduce(WordVectorConverter) - Method in class hex.word2vec.WordVectorConverter
reduce(WordVectorTrainer) - Method in class hex.word2vec.WordVectorTrainer
reducePrecision() - Method in class hex.tree.DHistogram: Cast bin values *except for sums of weights and Na-bucket counters to floats to drop least significant bits.
regex - Variable in class hex.schemas.GrepV3.GrepParametersV3
register(String) - Method in class hex.api.RegisterAlgos
RegisterAlgos - Class in hex.api
RegisterAlgos() - Constructor for class hex.api.RegisterAlgos
regression_stop - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3: The stopping criteria in terms of regression error (MSE) on the training data scoring dataset.
regression_stop - Variable in class hex.schemas.DeepWaterV3.DeepWaterParametersV3: The stopping criteria in terms of regression error (MSE) on the training data scoring dataset.
regularization_x - Variable in class hex.schemas.GLRMV3.GLRMParametersV3
regularization_y - Variable in class hex.schemas.GLRMV3.GLRMParametersV3
rel_improvement - Variable in class hex.optimization.L_BFGS.Result
rel_tol_num_exemplars - Variable in class hex.schemas.AggregatorV99.AggregatorParametersV99
remove_collinear_columns - Variable in class hex.schemas.GLMV3.GLMParametersV3
remove_impl(Futures) - Method in class hex.aggregator.AggregatorModel
remove_impl(Futures) - Method in class hex.deepwater.DeepWaterModel
remove_impl(Futures) - Method in class hex.glrm.GLRMModel
remove_impl(Futures) - Method in class hex.StackedEnsembleModel
remove_impl(Futures) - Method in class hex.svd.SVDModel
remove_impl(Futures) - Method in class hex.tree.SharedTreeModel
removeCols(int[]) - Method in class hex.glm.ComputationState
replicate_training_data - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3: Replicate the entire training dataset onto every node for faster training on small datasets.
replicate_training_data - Variable in class hex.schemas.DeepWaterV3.DeepWaterParametersV3: Replicate the entire training dataset onto every node for faster training on small datasets.
representation_name - Variable in class hex.schemas.GLRMModelV3.GLRMModelOutputV3
reproducible - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
resDOF() - Method in class hex.glm.GLMMetricBuilder
residualDeviance() - Method in class hex.glm.GLMMetricBuilder
response - Variable in class hex.DataInfo.Row
response(int) - Method in class hex.DataInfo.Row
response_bad - Variable in class hex.DataInfo.Row
responseChunkId(int) - Method in class hex.DataInfo
responseColumn - Variable in class hex.StackedEnsembleModel
responseIndex - Variable in class hex.tree.SharedTree.FrameMap
responseMeans() - Method in class hex.glm.GLMTask.YMUTask
responseSDs() - Method in class hex.glm.GLMTask.YMUTask
result - Variable in class hex.schemas.DataInfoFrameV3
resultSSE() - Method in class hex.tree.drf.TreeMeasuresCollector
resultVotes() - Method in class hex.tree.drf.TreeMeasuresCollector
resumeFromCheckpoint(SharedTree) - Method in class hex.tree.SharedTree.Driver: Restore the workspace from a previous model (checkpoint)
rho() - Method in class hex.glm.GLM.GramSolver
rho() - Method in class hex.glm.GLM.ProximalGradientSolver
rho() - Method in interface hex.optimization.ADMM.ProximalSolver
rho - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3: The first of two hyper parameters for adaptive learning rate (ADADELTA).
rid - Variable in class hex.DataInfo.Row
rms_weight - Variable in class hex.deeplearning.DeepLearningModelInfo
rngForChunk(int) - Method in class hex.tree.CompressedTree
root() - Method in class hex.tree.DTree
row(int) - Method in class hex.DataInfo.Rows
rows(Chunk[]) - Method in class hex.DataInfo
rows(Chunk[], boolean) - Method in class hex.DataInfo
rows() - Method in class hex.deeplearning.Storage.DenseColMatrix
rows() - Method in class hex.deeplearning.Storage.DenseRowMatrix
rows() - Method in interface hex.deeplearning.Storage.Matrix
rows() - Method in class hex.deeplearning.Storage.SparseRowMatrix
rows() - Method in interface hex.deeplearning.Storage.Tensor

S

Sample - Class in hex.tree
Sample(DTree, double, double[]) - Constructor for class hex.tree.Sample
sample_rate - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3
sample_rate_per_class - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3
schema() - Method in class hex.coxph.CoxPHModel
schema() - Method in class hex.deepwater.DeepWaterModel
schema() - Method in class hex.naivebayes.NaiveBayesModel
score(double[]) - Method in class hex.tree.CompressedTree
Score - Class in hex.tree: Score the tree columns, and produce a confusion matrix and AUC
Score(SharedTree, boolean, boolean, Key<Vec>, ModelCategory, boolean) - Constructor for class hex.tree.Score: Compute ModelMetrics on the testing dataset.
score0(double[], double[]) - Method in class hex.aggregator.AggregatorModel
score0(double[], double[]) - Method in class hex.coxph.CoxPHModel: Predict from raw double values representing the data
score0(double[], double[]) - Method in class hex.deeplearning.DeepLearningModel
score0(double[], double[], double) - Method in class hex.deeplearning.DeepLearningModel: Predict from raw double values representing the data
score0(double[], double[]) - Method in class hex.deepwater.DeepWaterModel: Single-instance scoring - slow, not optimized for mini-batches - do not use unless you know what you're doing
score0(double[], double[], double) - Method in class hex.deepwater.DeepWaterModel
score0(double[], double[]) - Method in class hex.example.ExampleModel
score0(double[], double[]) - Method in class hex.glm.GLMModel
score0(double[], double[], double) - Method in class hex.glm.GLMModel
score0(double[], double[]) - Method in class hex.glrm.GLRMModel
score0(double[], double[]) - Method in class hex.grep.GrepModel
score0(double[], double[], double) - Method in class hex.kmeans.KMeansModel
score0(double[], double[]) - Method in class hex.kmeans.KMeansModel
score0(double[], double[]) - Method in class hex.naivebayes.NaiveBayesModel
score0(double[], double[]) - Method in class hex.pca.PCAModel
score0(double[], double[]) - Method in class hex.StackedEnsembleModel: Should never be called: the code paths that normally go here should call predictScoreImpl().
score0(double[], double[]) - Method in class hex.svd.SVDModel
score0(double[], double[], double, int) - Method in class hex.tree.drf.DRFModel: Bulk scoring API for one row.
score0(double[], double[], CompressedTree[]) - Method in class hex.tree.DTreeScorer
score0(double[], double[], double, int) - Method in class hex.tree.gbm.GBMModel: Bulk scoring API for one row.
score0(double[], double[], double) - Method in class hex.tree.SharedTreeModel
score0(double[], double[]) - Method in class hex.tree.SharedTreeModel
score0(double[], double[], double, int) - Method in class hex.tree.SharedTreeModel
score0(Chunk[], int, double[], double[]) - Method in class hex.word2vec.Word2VecModel
score0(double[], double[]) - Method in class hex.word2vec.Word2VecModel
score1(Chunk[], double, double, double[], int) - Method in class hex.tree.drf.DRF
score1(Chunk[], double, double, double[], int) - Method in class hex.tree.gbm.GBM
score1(Chunk[], double, double, double[], int) - Method in class hex.tree.SharedTree
score_decide(Chunk[], Chunk, int[]) - Method in class hex.tree.ScoreBuildHistogram
score_decide(Chunk[], int[]) - Method in class hex.tree.ScoreBuildHistogram2
score_duty_cycle - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3: Maximum fraction of wall clock time spent on model scoring on training and validation samples, and on diagnostics such as computation of feature importances (i.e., not on training).
score_duty_cycle - Variable in class hex.schemas.DeepWaterV3.DeepWaterParametersV3: Maximum fraction of wall clock time spent on model scoring on training and validation samples, and on diagnostics such as computation of feature importances (i.e., not on training).
score_indicator(Chunk[], int, double[], double[]) - Method in class hex.kmeans.KMeansModel
score_interval - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3: The minimum time (in seconds) to elapse between model scoring.
score_interval - Variable in class hex.schemas.DeepWaterV3.DeepWaterParametersV3: The minimum time (in seconds) to elapse between model scoring.
score_ratio(Chunk[], int, double[]) - Method in class hex.kmeans.KMeansModel
score_training_samples - Variable in class hex.deeplearning.DeepLearningScoringInfo
score_training_samples() - Method in class hex.deeplearning.DeepLearningScoringInfo
score_training_samples() - Method in class hex.deepwater.DeepWaterScoringInfo
score_training_samples - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3: The number of training dataset points to be used for scoring.
score_training_samples - Variable in class hex.schemas.DeepWaterV3.DeepWaterParametersV3: The number of training dataset points to be used for scoring.
score_tree_interval - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3
score_validation_samples - Variable in class hex.deeplearning.DeepLearningScoringInfo
score_validation_samples() - Method in class hex.deeplearning.DeepLearningScoringInfo
score_validation_samples() - Method in class hex.deepwater.DeepWaterScoringInfo
score_validation_samples - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3: The number of validation dataset points to be used for scoring.
score_validation_samples - Variable in class hex.schemas.DeepWaterV3.DeepWaterParametersV3: The number of validation dataset points to be used for scoring.
score_validation_sampling - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3: Method used to sample the validation dataset for scoring, see Score Validation Samples above.
scoreAndBuildTrees(boolean) - Method in class hex.tree.SharedTree.Driver: Build more trees, as specified by the model parameters
scoreArchetypes(Frame, Key<Frame>, boolean) - Method in class hex.glrm.GLRMModel: Project each archetype into original feature space
scoreAutoEncoder(Frame, Key, boolean) - Method in class hex.deeplearning.DeepLearningModel: Score auto-encoded reconstruction (on-the-fly, without allocating the reconstruction as done in Frame score(Frame fr))
scoreAutoEncoder(Frame, Key, boolean) - Method in class hex.deepwater.DeepWaterModel
ScoreBuildHistogram - Class in hex.tree: Score and Build Histogram
ScoreBuildHistogram(H2O.H2OCountedCompleter, int, int, int, int, DTree, int, DHistogram[][], DistributionFamily, int, int, int) - Constructor for class hex.tree.ScoreBuildHistogram
ScoreBuildHistogram2 - Class in hex.tree: Created by tomas on 10/28/16.
ScoreBuildHistogram2(H2O.H2OCountedCompleter, int, int, int, int, DTree, int, DHistogram[][], DistributionFamily, int, int, int) - Constructor for class hex.tree.ScoreBuildHistogram2
scoreCols() - Method in class hex.tree.DTree.UndecidedNode
scoreDeepFeatures(Frame, int) - Method in class hex.deeplearning.DeepLearningModel: Score auto-encoded reconstruction (on-the-fly, and materialize the deep features of given layer
scoreDeepFeatures(Frame, int, Job) - Method in class hex.deeplearning.DeepLearningModel
scoreDeepFeatures(Frame, String, Job) - Method in class hex.deeplearning.DeepLearningModel
scoreDeepFeatures(Frame, int) - Method in class hex.deepwater.DeepWaterModel
scoreDeepFeatures(Frame, int, Job) - Method in class hex.deepwater.DeepWaterModel
scoreDeepFeatures(Frame, String, Job) - Method in class hex.deepwater.DeepWaterModel
scoreExemplarMembers(Key<Frame>, int) - Method in class hex.aggregator.AggregatorModel
scoreKeepers() - Method in class hex.tree.SharedTreeModel.SharedTreeOutput
scoreLeafNodeAssignment(Frame, Key<Frame>) - Method in class hex.tree.SharedTreeModel
scoreMetrics(Frame) - Method in class hex.deepwater.DeepWaterModel
scoreMetrics(Frame) - Method in class hex.glm.GLMModel: Score an already adapted frame.
scoreMetricsOnly(Frame) - Method in class hex.glrm.GLRMModel
scoreReconstruction(Frame, Key<Frame>, boolean) - Method in class hex.glrm.GLRMModel
scoreRow(DataInfo.Row, double, double[]) - Method in class hex.glm.GLMScore
scores - Variable in class hex.schemas.Word2VecSynonymsV3
scoreTree(double[], double[], CompressedTree[]) - Static method in class hex.tree.DTreeScorer: Score given tree on the row of data.
scoreZeroTrees() - Method in class hex.tree.drf.DRF
scoreZeroTrees() - Method in class hex.tree.SharedTree
SCORING_INTERVAL_MSEC - Static variable in class hex.glm.GLM
scoringDomains() - Method in class hex.glm.GLMModel
scoringInfo(String[], Frame) - Method in class hex.DataInfo
se() - Method in class hex.tree.DTree.Split
seed - Variable in class hex.schemas.AggregatorV99.AggregatorParametersV99
seed - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3: The random seed controls sampling and initialization.
seed - Variable in class hex.schemas.DeepWaterV3.DeepWaterParametersV3: The random seed controls sampling and initialization.
seed - Variable in class hex.schemas.GLMV3.GLMParametersV3
seed - Variable in class hex.schemas.GLRMV3.GLRMParametersV3
seed - Variable in class hex.schemas.KMeansV3.KMeansParametersV3
seed - Variable in class hex.schemas.NaiveBayesV3.NaiveBayesParametersV3
seed - Variable in class hex.schemas.PCAV3.PCAParametersV3
seed - Variable in class hex.schemas.SharedTreeV3.SharedTreeParametersV3
seed - Variable in class hex.schemas.SVDV99.SVDParametersV99
seed - Variable in class hex.StackedEnsembleModel
seed(int) - Static method in class hex.tree.drf.TreeMeasuresCollector.ShuffleTask
sent_sample_rate - Variable in class hex.schemas.Word2VecV3.Word2VecParametersV3
set(int, int, float) - Method in class hex.deeplearning.Storage.DenseColMatrix
set(int, int, float) - Method in class hex.deeplearning.Storage.DenseRowMatrix
set(int, double) - Method in class hex.deeplearning.Storage.DenseVector
set(int, int, float) - Method in interface hex.deeplearning.Storage.Matrix
set(int, int, float) - Method in class hex.deeplearning.Storage.SparseRowMatrix
set(int, int, int, float) - Method in interface hex.deeplearning.Storage.Tensor
set(int, double) - Method in interface hex.deeplearning.Storage.Vector
set_params(DeepLearningModel.DeepLearningParameters, Key<Model>) - Method in class hex.deeplearning.DeepLearningModelInfo
set_processed_global(long) - Method in class hex.deeplearning.DeepLearningModelInfo
set_processed_local(long) - Method in class hex.deeplearning.DeepLearningModelInfo
setActiveClass(int) - Method in class hex.glm.ComputationState
setBC(GLM.BetaConstraint) - Method in class hex.glm.ComputationState
setBetaMultinomial(int, double[], double[]) - Method in class hex.glm.ComputationState
setCatNAFill(int[]) - Method in class hex.DataInfo
setGradEps(double) - Method in class hex.optimization.L_BFGS
setGradientNorm(MathUtils.Norm) - Method in class hex.optimization.ADMM.L1Solver
setHistorySz(int) - Method in class hex.optimization.L_BFGS
setInitialStep(double) - Method in interface hex.optimization.OptimizationUtils.LineSearchSolver
setInitialStep(double) - Method in class hex.optimization.OptimizationUtils.MoreThuente
setInitialStep(double) - Method in class hex.optimization.OptimizationUtils.SimpleBacktrackingLS
setInput(long, double[], int) - Method in class hex.deeplearning.Neurons.Input: One of two methods to set layer input values.
setInput(long, int[], double[], int, int[], int) - Method in class hex.deeplearning.Neurons.Input: The second method used to set input layer values.
setLambda(double) - Method in class hex.glm.ComputationState
setLambdaMax(double) - Method in class hex.glm.ComputationState
setMaxIn(double) - Method in class hex.tree.DHistogram
setMaxIter(int) - Method in class hex.optimization.L_BFGS
setMin(double) - Method in class hex.tree.DHistogram
setNonNegative() - Method in class hex.glm.GLM.BetaConstraint
setNumTrees(int) - Method in class hex.tree.TreeStats
setObjEps(double) - Method in class hex.optimization.L_BFGS
setOutput(int, double) - Method in class hex.DataInfo.Row
setOutputLayerGradient(double, int, int) - Method in class hex.deeplearning.Neurons.Linear: Backpropagation for regression
setOutputLayerGradient(double, int, int) - Method in class hex.deeplearning.Neurons: Accumulation of reconstruction errors for a generic Neurons class (This is only used for AutoEncoders)
setOutputLayerGradient(double, int, int) - Method in class hex.deeplearning.Neurons.Softmax: Part of backpropagation for classification Update every weight as follows: w += -rate * dE/dw Compute dE/dw via chain rule: dE/dw = dE/dy * dy/dnet * dnet/dw, where net = sum(xi*wi)+b and y = activation function
setPredictorTransform(DataInfo.TransformType) - Method in class hex.DataInfo
setResponse(int, double) - Method in class hex.DataInfo.Row
setResponse(String, Vec) - Method in class hex.DataInfo
setResponse(String, Vec, int) - Method in class hex.DataInfo
setResponseTransform(DataInfo.TransformType) - Method in class hex.DataInfo
setSparse(boolean) - Method in class hex.FrameTask2
setSPD(boolean) - Method in class hex.gram.Gram.Cholesky
setSubmodel(double) - Method in class hex.glm.GLMModel.GLMOutput
setSubmodelIdx(int) - Method in class hex.glm.GLMModel.GLMOutput
setUnstable() - Method in class hex.deeplearning.DeepLearningModelInfo
setupBigScorePredict() - Method in class hex.deepwater.DeepWaterModel
setupLocal() - Method in class hex.deeplearning.DeepLearningTask: Transfer ownership from global (shared) model to local model which will be worked on
setupLocal() - Method in class hex.deeplearning.DeepLearningTask2: Do the local computation: Perform one DeepLearningTask (with run_local=true) iteration.
setupLocal() - Method in class hex.deepwater.DeepWaterTask: Transfer ownership from global (shared) model to local model which will be worked on
setupLocal() - Method in class hex.FrameTask
setupLocal() - Method in class hex.FrameTask2
setupLocal() - Method in class hex.glm.GLMTask.YMUTask
setupLocal() - Method in class hex.tree.DTreeScorer
setupLocal() - Method in class hex.tree.ScoreBuildHistogram
setupLocal() - Method in class hex.tree.ScoreBuildHistogram2
setupLocal() - Method in class hex.word2vec.WordVectorConverter
setupLocal() - Method in class hex.word2vec.WordVectorTrainer
setVcov(double[][]) - Method in class hex.glm.GLMModel
setWeights(String, Vec) - Method in class hex.DataInfo
setWideDataset(boolean) - Method in class hex.pca.PCA
setWideDataset(boolean) - Method in class hex.svd.SVD
setZValues(double[], double, boolean) - Method in class hex.glm.GLMModel
SharedTree<M extends SharedTreeModel<M,P,O>,P extends SharedTreeModel.SharedTreeParameters,O extends SharedTreeModel.SharedTreeOutput> - Class in hex.tree
SharedTree(P) - Constructor for class hex.tree.SharedTree
SharedTree(P, Key<M>) - Constructor for class hex.tree.SharedTree
SharedTree(P, Job) - Constructor for class hex.tree.SharedTree
SharedTree(P, boolean) - Constructor for class hex.tree.SharedTree
SharedTree.Driver - Class in hex.tree
SharedTree.Driver() - Constructor for class hex.tree.SharedTree.Driver
SharedTree.FrameMap - Class in hex.tree
SharedTree.FrameMap() - Constructor for class hex.tree.SharedTree.FrameMap
SharedTree.FrameMap(SharedTree) - Constructor for class hex.tree.SharedTree.FrameMap
SharedTreeModel<M extends SharedTreeModel<M,P,O>,P extends SharedTreeModel.SharedTreeParameters,O extends SharedTreeModel.SharedTreeOutput> - Class in hex.tree
SharedTreeModel(Key<M>, P, O) - Constructor for class hex.tree.SharedTreeModel
SharedTreeModel.SharedTreeOutput - Class in hex.tree
SharedTreeModel.SharedTreeOutput(SharedTree) - Constructor for class hex.tree.SharedTreeModel.SharedTreeOutput
SharedTreeModel.SharedTreeParameters - Class in hex.tree
SharedTreeModel.SharedTreeParameters() - Constructor for class hex.tree.SharedTreeModel.SharedTreeParameters
SharedTreeModel.SharedTreeParameters.HistogramType - Enum in hex.tree
SharedTreeModelV3<M extends SharedTreeModel<M,P,O>,S extends SharedTreeModelV3<M,S,P,PS,O,OS>,P extends SharedTreeModel.SharedTreeParameters,PS extends SharedTreeV3.SharedTreeParametersV3<P,PS>,O extends SharedTreeModel.SharedTreeOutput,OS extends SharedTreeModelV3.SharedTreeModelOutputV3<O,OS>> - Class in hex.schemas
SharedTreeModelV3() - Constructor for class hex.schemas.SharedTreeModelV3
SharedTreeModelV3.SharedTreeModelOutputV3<O extends SharedTreeModel.SharedTreeOutput,SO extends SharedTreeModelV3.SharedTreeModelOutputV3<O,SO>> - Class in hex.schemas
SharedTreeModelV3.SharedTreeModelOutputV3() - Constructor for class hex.schemas.SharedTreeModelV3.SharedTreeModelOutputV3
SharedTreeMojoWriter<M extends SharedTreeModel<M,P,O>,P extends SharedTreeModel.SharedTreeParameters,O extends SharedTreeModel.SharedTreeOutput> - Class in hex.tree: Shared Mojo definition file for DRF and GBM models.
SharedTreeMojoWriter() - Constructor for class hex.tree.SharedTreeMojoWriter
SharedTreeMojoWriter(M) - Constructor for class hex.tree.SharedTreeMojoWriter
SharedTreeV3<B extends SharedTree,S extends SharedTreeV3<B,S,P>,P extends SharedTreeV3.SharedTreeParametersV3> - Class in hex.schemas
SharedTreeV3() - Constructor for class hex.schemas.SharedTreeV3
SharedTreeV3.SharedTreeParametersV3<P extends SharedTreeModel.SharedTreeParameters,S extends SharedTreeV3.SharedTreeParametersV3<P,S>> - Class in hex.schemas
SharedTreeV3.SharedTreeParametersV3() - Constructor for class hex.schemas.SharedTreeV3.SharedTreeParametersV3
shouldReorder(Vec) - Method in class hex.tree.SharedTree
shrinkage(double, double) - Static method in class hex.optimization.ADMM
shuffle(Vec) - Static method in class hex.tree.drf.TreeMeasuresCollector.ShuffleTask
shuffle_training_data - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3: Enable shuffling of training data (on each node).
shuffle_training_data - Variable in class hex.schemas.DeepWaterV3.DeepWaterParametersV3: Enable shuffling of training data (on each node).
ShuffleSplitFrame - Class in hex.splitframe: Frame splitter function to divide given frame into multiple partitions based on given ratios.
ShuffleSplitFrame() - Constructor for class hex.splitframe.ShuffleSplitFrame
shuffleSplitFrame(Frame, Key<Frame>[], double[], long) - Static method in class hex.splitframe.ShuffleSplitFrame
single_node_mode - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3: Run on a single node for fine-tuning of model parameters.
single_node_mode - Variable in class hex.schemas.DeepWaterV3.DeepWaterParametersV3: Run on a single node for fine-tuning of model parameters.
singular_vals - Variable in class hex.schemas.GLRMModelV3.GLRMModelOutputV3
size() - Method in class hex.deeplearning.DeepLearningModelInfo
size() - Method in class hex.deeplearning.Storage.DenseColMatrix
size() - Method in class hex.deeplearning.Storage.DenseRowMatrix
size() - Method in class hex.deeplearning.Storage.DenseVector
size() - Method in interface hex.deeplearning.Storage.Matrix
size() - Method in class hex.deeplearning.Storage.SparseRowMatrix
size() - Method in interface hex.deeplearning.Storage.Tensor
size() - Method in interface hex.deeplearning.Storage.Vector
size() - Method in class hex.deepwater.DeepWaterModelInfo
size() - Method in class hex.tree.DTree.DecidedNode
size() - Method in class hex.tree.DTree.LeafNode
size() - Method in class hex.tree.DTree.Node
size() - Method in class hex.tree.DTree.UndecidedNode
sizeCensored - Variable in class hex.coxph.CoxPH.CoxPHTask
sizeEvents - Variable in class hex.coxph.CoxPH.CoxPHTask
sizeRiskSet - Variable in class hex.coxph.CoxPH.CoxPHTask
skip_missing - Variable in class hex.schemas.GramV3
slices() - Method in interface hex.deeplearning.Storage.Tensor
solve(double[]) - Method in class hex.glm.GLM.GramSolver
solve(double[], double[]) - Method in class hex.glm.GLM.GramSolver
solve(double[], double[]) - Method in class hex.glm.GLM.ProximalGradientSolver
solve(double[][]) - Method in class hex.gram.Gram.Cholesky
solve(double[]) - Method in class hex.gram.Gram.Cholesky: Find solution to A*x = y.
solve(ADMM.ProximalSolver, double[], double, boolean) - Method in class hex.optimization.ADMM.L1Solver
solve(ADMM.ProximalSolver, double[], double, boolean, double[], double[]) - Method in class hex.optimization.ADMM.L1Solver
solve(double[], double[]) - Method in interface hex.optimization.ADMM.ProximalSolver
solve(OptimizationUtils.GradientSolver, double[], OptimizationUtils.GradientInfo, L_BFGS.ProgressMonitor) - Method in class hex.optimization.L_BFGS: Solve the optimization problem defined by the user-supplied ginfo function using L-BFGS algorithm.
solve(OptimizationUtils.GradientSolver, double[]) - Method in class hex.optimization.L_BFGS: Solve the optimization problem defined by the user-supplied ginfo function using L-BFGS algorithm.
solver - Variable in class hex.schemas.GLMV3.GLMParametersV3
sparse - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
sparse - Variable in class hex.schemas.DeepWaterV3.DeepWaterParametersV3
sparseness() - Method in class hex.gram.Gram
sparseOffset(double[], DataInfo) - Static method in class hex.glm.GLM
sparsity_beta - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
StackedEnsemble - Class in hex.ensemble: An ensemble of other models, created by stacking with the SuperLearner algorithm or a variation.
StackedEnsemble(StackedEnsembleModel.StackedEnsembleParameters) - Constructor for class hex.ensemble.StackedEnsemble
StackedEnsemble(boolean) - Constructor for class hex.ensemble.StackedEnsemble
StackedEnsembleModel - Class in hex: An ensemble of other models, created by stacking with the SuperLearner algorithm or a variation.
StackedEnsembleModel(Key, StackedEnsembleModel.StackedEnsembleParameters, StackedEnsembleModel.StackedEnsembleOutput) - Constructor for class hex.StackedEnsembleModel
StackedEnsembleModel.StackedEnsembleOutput - Class in hex
StackedEnsembleModel.StackedEnsembleOutput() - Constructor for class hex.StackedEnsembleModel.StackedEnsembleOutput
StackedEnsembleModel.StackedEnsembleOutput(StackedEnsemble) - Constructor for class hex.StackedEnsembleModel.StackedEnsembleOutput
StackedEnsembleModel.StackedEnsembleOutput(Job) - Constructor for class hex.StackedEnsembleModel.StackedEnsembleOutput
StackedEnsembleModel.StackedEnsembleParameters - Class in hex
StackedEnsembleModel.StackedEnsembleParameters() - Constructor for class hex.StackedEnsembleModel.StackedEnsembleParameters
StackedEnsembleModelV99 - Class in hex.schemas: Created by rpeck on 10/11/16.
StackedEnsembleModelV99() - Constructor for class hex.schemas.StackedEnsembleModelV99
StackedEnsembleModelV99.StackedEnsembleModelOutputV99 - Class in hex.schemas
StackedEnsembleModelV99.StackedEnsembleModelOutputV99() - Constructor for class hex.schemas.StackedEnsembleModelV99.StackedEnsembleModelOutputV99
StackedEnsembleV99 - Class in hex.schemas: Created by rpeck on 10/11/16.
StackedEnsembleV99() - Constructor for class hex.schemas.StackedEnsembleV99
StackedEnsembleV99.StackedEnsembleParametersV99 - Class in hex.schemas
StackedEnsembleV99.StackedEnsembleParametersV99() - Constructor for class hex.schemas.StackedEnsembleV99.StackedEnsembleParametersV99
standardize(double[], double[]) - Method in class hex.DataInfo.Row
standardize - Variable in class hex.schemas.DataInfoFrameV3
standardize - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
standardize - Variable in class hex.schemas.DeepWaterV3.DeepWaterParametersV3
standardize - Variable in class hex.schemas.GLMV3.GLMParametersV3
standardize - Variable in class hex.schemas.GramV3
standardize - Variable in class hex.schemas.KMeansV3.KMeansParametersV3
start_column - Variable in class hex.coxph.CoxPHModel.CoxPHParameters
startCoefs(int, long) - Static method in class hex.optimization.L_BFGS
stdErr() - Method in class hex.glm.GLMModel.GLMOutput
step() - Method in interface hex.optimization.OptimizationUtils.LineSearchSolver
step() - Method in class hex.optimization.OptimizationUtils.MoreThuente
step() - Method in class hex.optimization.OptimizationUtils.SimpleBacktrackingLS
step_size - Variable in class hex.schemas.GLRMModelV3.GLRMModelOutputV3
stop_column - Variable in class hex.coxph.CoxPHModel.CoxPHParameters
stopped_early - Variable in class hex.deeplearning.DeepLearningModel
Storage - Class in hex.deeplearning
Storage() - Constructor for class hex.deeplearning.Storage
Storage.DenseColMatrix - Class in hex.deeplearning: Dense column matrix implementation
Storage.DenseRowMatrix - Class in hex.deeplearning: Dense row matrix implementation
Storage.DenseVector - Class in hex.deeplearning: Dense vector implementation
Storage.Matrix - Interface in hex.deeplearning: Abstract matrix interface
Storage.SparseRowMatrix - Class in hex.deeplearning: Sparse row matrix implementation
Storage.Tensor - Interface in hex.deeplearning: Abstract tensor interface
Storage.Vector - Interface in hex.deeplearning: Abstract vector interface
str() - Method in class water.rapids.prims.word2vec.AstWord2VecToFrame
subgrad(double, double[], double[]) - Static method in class hex.optimization.ADMM
sumLogRiskEvents - Variable in class hex.coxph.CoxPH.CoxPHTask
summaryTable - Variable in class hex.deeplearning.DeepLearningModelInfo
sumRiskEvents - Variable in class hex.coxph.CoxPH.CoxPHTask
sumWeightedCatX - Variable in class hex.coxph.CoxPH.CoxPHTask
sumWeightedNumX - Variable in class hex.coxph.CoxPH.CoxPHTask
sumWeights - Variable in class hex.coxph.CoxPH.CoxPHTask
sumXEvents - Variable in class hex.coxph.CoxPH.CoxPHTask
sumXRiskEvents - Variable in class hex.coxph.CoxPH.CoxPHTask
sumXXRiskEvents - Variable in class hex.coxph.CoxPH.CoxPHTask
SVD - Class in hex.svd: Singular Value Decomposition SVD via Power Method Algorithm Proof of Convergence for Power Method Randomized Algorithms for Matrix Approximation
SVD(SVDModel.SVDParameters) - Constructor for class hex.svd.SVD
SVD(SVDModel.SVDParameters, Job) - Constructor for class hex.svd.SVD
SVD(SVDModel.SVDParameters, Job, boolean, GLRMModel) - Constructor for class hex.svd.SVD
SVD(boolean) - Constructor for class hex.svd.SVD
svd_method - Variable in class hex.schemas.GLRMV3.GLRMParametersV3
svd_method - Variable in class hex.schemas.SVDV99.SVDParametersV99
SVDModel - Class in hex.svd
SVDModel(Key<SVDModel>, SVDModel.SVDParameters, SVDModel.SVDOutput) - Constructor for class hex.svd.SVDModel
SVDModel.ModelMetricsSVD - Class in hex.svd
SVDModel.ModelMetricsSVD(Model, Frame) - Constructor for class hex.svd.SVDModel.ModelMetricsSVD
SVDModel.ModelMetricsSVD.SVDModelMetrics - Class in hex.svd
SVDModel.ModelMetricsSVD.SVDModelMetrics(int) - Constructor for class hex.svd.SVDModel.ModelMetricsSVD.SVDModelMetrics
SVDModel.SVDOutput - Class in hex.svd
SVDModel.SVDOutput(SVD) - Constructor for class hex.svd.SVDModel.SVDOutput
SVDModel.SVDParameters - Class in hex.svd
SVDModel.SVDParameters() - Constructor for class hex.svd.SVDModel.SVDParameters
SVDModel.SVDParameters.Method - Enum in hex.svd
SVDModelV99 - Class in hex.schemas
SVDModelV99() - Constructor for class hex.schemas.SVDModelV99
SVDModelV99.SVDModelOutputV99 - Class in hex.schemas
SVDModelV99.SVDModelOutputV99() - Constructor for class hex.schemas.SVDModelV99.SVDModelOutputV99
SVDV99 - Class in hex.schemas
SVDV99() - Constructor for class hex.schemas.SVDV99
SVDV99.SVDParametersV99 - Class in hex.schemas
SVDV99.SVDParametersV99() - Constructor for class hex.schemas.SVDV99.SVDParametersV99
synonyms - Variable in class hex.schemas.Word2VecSynonymsV3

T

target_num_exemplars - Variable in class hex.schemas.AggregatorV99.AggregatorParametersV99
target_ratio_comm_to_comp - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
target_ratio_comm_to_comp - Variable in class hex.schemas.DeepWaterV3.DeepWaterParametersV3
threshold - Variable in class hex.schemas.MakeGLMModelV3
ties - Variable in class hex.coxph.CoxPHModel.CoxPHParameters
time_for_communication_us - Variable in class hex.deeplearning.DeepLearningModel
timeAverage(DeepLearningModelInfo) - Static method in class hex.deeplearning.DeepLearningModelInfo: TimeAveraging as part of Elastic Averaging Algorithm Cf.
toEigen - Static variable in class hex.util.LinearAlgebraUtils
toEigen(Vec) - Static method in class hex.util.LinearAlgebraUtils
toFrame(Key) - Method in class hex.deeplearning.Storage.DenseColMatrix
toFrame(Key) - Method in class hex.deeplearning.Storage.DenseRowMatrix
toFrame(Key) - Method in class hex.deeplearning.Storage.DenseVector
toFrame(Key) - Method in interface hex.deeplearning.Storage.Matrix
toFrame(Key) - Method in class hex.deeplearning.Storage.SparseRowMatrix
toFrame(int, Key) - Method in interface hex.deeplearning.Storage.Tensor
toFrame(Key) - Method in interface hex.deeplearning.Storage.Vector
toFrame() - Method in class hex.word2vec.Word2VecModel: Converts this word2vec model to a Frame.
toJavaCheckTooBig() - Method in class hex.deeplearning.DeepLearningModel
toJavaCheckTooBig() - Method in class hex.glm.GLMModel
toJavaCheckTooBig() - Method in class hex.kmeans.KMeansModel
toJavaCheckTooBig() - Method in class hex.tree.SharedTreeModel
toJavaForestName(T, String, int) - Method in class hex.tree.SharedTreeModel
toJavaInit(SBPrintStream, CodeGeneratorPipeline) - Method in class hex.deeplearning.DeepLearningModel
toJavaInit(SBPrintStream, CodeGeneratorPipeline) - Method in class hex.glm.GLMModel
toJavaInit(SBPrintStream, CodeGeneratorPipeline) - Method in class hex.naivebayes.NaiveBayesModel
toJavaInit(SBPrintStream, CodeGeneratorPipeline) - Method in class hex.pca.PCAModel
toJavaInit(SBPrintStream, CodeGeneratorPipeline) - Method in class hex.svd.SVDModel
toJavaInit(SBPrintStream, CodeGeneratorPipeline) - Method in class hex.tree.SharedTreeModel
toJavaPredictBody(SBPrintStream, CodeGeneratorPipeline, CodeGeneratorPipeline, boolean) - Method in class hex.deeplearning.DeepLearningModel
toJavaPredictBody(SBPrintStream, CodeGeneratorPipeline, CodeGeneratorPipeline, boolean) - Method in class hex.glm.GLMModel
toJavaPredictBody(SBPrintStream, CodeGeneratorPipeline, CodeGeneratorPipeline, boolean) - Method in class hex.kmeans.KMeansModel
toJavaPredictBody(SBPrintStream, CodeGeneratorPipeline, CodeGeneratorPipeline, boolean) - Method in class hex.naivebayes.NaiveBayesModel
toJavaPredictBody(SBPrintStream, CodeGeneratorPipeline, CodeGeneratorPipeline, boolean) - Method in class hex.pca.PCAModel
toJavaPredictBody(SBPrintStream, CodeGeneratorPipeline, CodeGeneratorPipeline, boolean) - Method in class hex.svd.SVDModel
toJavaPredictBody(SBPrintStream, CodeGeneratorPipeline, CodeGeneratorPipeline, boolean) - Method in class hex.tree.SharedTreeModel
toJavaTreeName(T, String, int, int) - Method in class hex.tree.SharedTreeModel
toJavaUnifyPreds(SBPrintStream) - Method in class hex.tree.drf.DRFModel
toJavaUnifyPreds(SBPrintStream) - Method in class hex.tree.gbm.GBMModel
toJavaUnifyPreds(SBPrintStream) - Method in class hex.tree.SharedTreeModel
toString() - Method in class hex.coxph.CoxPHModel
toString() - Method in class hex.DataInfo.Row
toString() - Method in class hex.deeplearning.DeepLearningModelInfo: Print a summary table
toString() - Method in class hex.deeplearning.Dropout
toString() - Method in class hex.deeplearning.Neurons: Print the status of this neuron layer
toString() - Method in class hex.deepwater.DeepWaterModelInfo: Print a summary table
toString() - Method in class hex.glm.ComputationState
toString() - Method in class hex.glm.GLM.BetaConstraint
toString() - Method in class hex.glm.GLM.GLMGradientInfo
toString() - Method in class hex.gram.Gram
toString() - Method in class hex.optimization.ADMM.L1Solver
toString() - Method in class hex.optimization.L_BFGS.Result
toString() - Method in class hex.optimization.OptimizationUtils.GradientInfo
toString() - Method in class hex.optimization.OptimizationUtils.MoreThuente
toString() - Method in class hex.optimization.OptimizationUtils.SimpleBacktrackingLS
toString(SharedTreeModel.SharedTreeOutput) - Method in class hex.tree.CompressedTree
toString() - Method in class hex.tree.DHistogram
toString() - Method in class hex.tree.DTree.DecidedNode
toString() - Method in class hex.tree.DTree.LeafNode
toString() - Method in class hex.tree.DTree.Split
toString() - Method in class hex.tree.DTree.UndecidedNode
toString() - Method in class hex.tree.TreeStats
toString2(StringBuilder, int) - Method in class hex.tree.DTree.DecidedNode
toString2(StringBuilder, int) - Method in class hex.tree.DTree.LeafNode
toString2(StringBuilder, int) - Method in class hex.tree.DTree.Node
toString2(StringBuilder, int) - Method in class hex.tree.DTree.UndecidedNode
toStringAll() - Method in class hex.coxph.CoxPHModel
toStringAll() - Method in class hex.deeplearning.DeepLearningModelInfo: Debugging printout
toStringAll() - Method in class hex.deepwater.DeepWaterModelInfo: Debugging printout
toStringTree(int, int) - Method in class hex.tree.SharedTreeModel.SharedTreeOutput
total_checkpointed_run_time_ms - Variable in class hex.deeplearning.DeepLearningModel
total_scoring_time_ms - Variable in class hex.deeplearning.DeepLearningModel
total_setup_time_ms - Variable in class hex.deeplearning.DeepLearningModel
total_training_time_ms - Variable in class hex.deeplearning.DeepLearningModel
train_samples_per_iteration - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3: The number of training data rows to be processed per iteration.
train_samples_per_iteration - Variable in class hex.schemas.DeepWaterV3.DeepWaterParametersV3: The number of training data rows to be processed per iteration.
training_rows - Variable in class hex.deeplearning.DeepLearningModel
training_samples - Variable in class hex.deeplearning.DeepLearningScoringInfo
training_samples() - Method in class hex.deeplearning.DeepLearningScoringInfo
training_samples() - Method in class hex.deepwater.DeepWaterScoringInfo
trainingFrameChecksum - Variable in class hex.StackedEnsembleModel
trainModel(DeepLearningModel) - Method in class hex.deeplearning.DeepLearning.DeepLearningDriver: Train a Deep Learning neural net model
trainModel(DeepWaterModel) - Method in class hex.deepwater.DeepWater.DeepWaterDriver: Train a Deep Learning neural net model
trainModelImpl() - Method in class hex.aggregator.Aggregator
trainModelImpl() - Method in class hex.coxph.CoxPH
trainModelImpl() - Method in class hex.deeplearning.DeepLearning
trainModelImpl() - Method in class hex.deepwater.DeepWater
trainModelImpl() - Method in class hex.ensemble.StackedEnsemble
trainModelImpl() - Method in class hex.example.Example
trainModelImpl() - Method in class hex.glm.GLM
trainModelImpl() - Method in class hex.glrm.GLRM
trainModelImpl() - Method in class hex.grep.Grep
trainModelImpl() - Method in class hex.kmeans.KMeans: Start the KMeans training Job on an F/J thread.
trainModelImpl() - Method in class hex.naivebayes.NaiveBayes
trainModelImpl() - Method in class hex.pca.PCA
trainModelImpl() - Method in class hex.svd.SVD
trainModelImpl() - Method in class hex.tree.drf.DRF: Start the DRF training Job on an F/J thread.
trainModelImpl() - Method in class hex.tree.gbm.GBM: Start the GBM training Job on an F/J thread.
trainModelImpl() - Method in class hex.word2vec.Word2Vec
transform(int, Word2VecTransformV3) - Method in class hex.api.Word2VecHandler
transform(double[][], double[], double[], int, int) - Static method in class hex.glrm.GLRM
transform - Variable in class hex.schemas.AggregatorV99.AggregatorParametersV99
transform - Variable in class hex.schemas.GLRMV3.GLRMParametersV3
transform - Variable in class hex.schemas.PCAV3.PCAParametersV3
transform - Variable in class hex.schemas.SVDV99.SVDParametersV99
transform(String) - Method in class hex.word2vec.Word2VecModel: Takes an input string can return the word vector for that word.
transform(Vec, Word2VecModel.AggregateMethod) - Method in class hex.word2vec.Word2VecModel
transformEigenVectors(DataInfo, double[][]) - Static method in class hex.util.DimensionReductionUtils: This function will tranform the eigenvectors calculated for a matrix T(A) to the ones calculated for matrix A.
tree0Index - Variable in class hex.tree.SharedTree.FrameMap
TreeMeasuresCollector - Class in hex.tree.drf: Score given tree model and preserve errors per tree in form of votes (for classification) or MSE (for regression).
TreeMeasuresCollector.ShuffleTask - Class in hex.tree.drf
TreeMeasuresCollector.ShuffleTask() - Constructor for class hex.tree.drf.TreeMeasuresCollector.ShuffleTask
TreeMeasuresCollector.TreeMeasures<T extends TreeMeasuresCollector.TreeMeasures> - Class in hex.tree.drf: A simple holder for set of different tree measurements.
TreeMeasuresCollector.TreeMeasures(int) - Constructor for class hex.tree.drf.TreeMeasuresCollector.TreeMeasures
TreeMeasuresCollector.TreeMeasures(double[], int) - Constructor for class hex.tree.drf.TreeMeasuresCollector.TreeMeasures
TreeMeasuresCollector.TreeSSE - Class in hex.tree.drf: A simple holder serving SSE per tree.
TreeMeasuresCollector.TreeSSE(int) - Constructor for class hex.tree.drf.TreeMeasuresCollector.TreeSSE
TreeMeasuresCollector.TreeSSE(float[], double[], int) - Constructor for class hex.tree.drf.TreeMeasuresCollector.TreeSSE
TreeMeasuresCollector.TreeVotes - Class in hex.tree.drf: A class holding tree votes.
TreeMeasuresCollector.TreeVotes(int) - Constructor for class hex.tree.drf.TreeMeasuresCollector.TreeVotes
TreeMeasuresCollector.TreeVotes(double[], double[], int) - Constructor for class hex.tree.drf.TreeMeasuresCollector.TreeVotes
TreeStats - Class in hex.tree
TreeStats() - Constructor for class hex.tree.TreeStats
TreeStatsV3 - Class in hex.schemas
TreeStatsV3() - Constructor for class hex.schemas.TreeStatsV3
TreeVisitor<T extends java.lang.Exception> - Class in hex.tree: Abstract visitor class for serialized trees.
TreeVisitor(CompressedTree) - Constructor for class hex.tree.TreeVisitor
trim(Aggregator.Exemplar[]) - Static method in class hex.aggregator.Aggregator.Exemplar: Trim any training nulls
tweedie_link_power - Variable in class hex.schemas.GLMV3.GLMParametersV3
tweedie_variance_power - Variable in class hex.schemas.GLMV3.GLMParametersV3

U

u_key - Variable in class hex.schemas.SVDModelV99.SVDModelOutputV99
u_name - Variable in class hex.schemas.SVDV99.SVDParametersV99
undecided(int) - Method in class hex.tree.DTree
UNDECIDED_CHILD_NODE_ID - Static variable in class hex.tree.ScoreBuildHistogram: Marker for a fresh tree
unit_active(int) - Method in class hex.deeplearning.Dropout
units - Variable in class hex.deeplearning.Neurons
unScaleNumericals(double[], double[]) - Method in class hex.DataInfo: Undo the standardization/normalization of numerical columns
update(double[], double, double, int) - Method in class hex.glm.GLMModel
updateBy(DTree) - Method in class hex.tree.TreeStats
updateHisto(double[], double[], double[], int[], int, int) - Method in class hex.tree.DHistogram: Update counts in appropriate bins.
updateIVVSum(double[][], double[]) - Static method in class hex.svd.SVD
updateModelInfo(Word2VecModel.Word2VecModelInfo) - Method in class hex.word2vec.WordVectorTrainer
updateProgress(boolean) - Method in class hex.glm.GLM.GLMDriver
updates - Variable in class hex.schemas.GLRMModelV3.GLRMModelOutputV3
updateSharedHistosAndReset(ScoreBuildHistogram.LocalHisto, double[], double[], double[], int[], int, int) - Method in class hex.tree.DHistogram
updateState(double[], double) - Method in class hex.glm.ComputationState
updateState(double[], GLM.GLMGradientInfo) - Method in class hex.glm.ComputationState
updateSubmodel(GLMModel.Submodel) - Method in class hex.glm.GLMModel
updateWeightedSigmaAndMean(double[], double[]) - Method in class hex.DataInfo
updateWeightedSigmaAndMeanForResponse(double[], double[]) - Method in class hex.DataInfo
use_all - Variable in class hex.schemas.DataInfoFrameV3
use_all_factor_levels - Variable in class hex.schemas.AggregatorV99.AggregatorParametersV99
use_all_factor_levels - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3
use_all_factor_levels - Variable in class hex.schemas.GramV3
use_all_factor_levels - Variable in class hex.schemas.PCAV3.PCAParametersV3
use_all_factor_levels - Variable in class hex.schemas.SVDV99.SVDParametersV99
user_points - Variable in class hex.schemas.KMeansV3.KMeansParametersV3
user_x - Variable in class hex.schemas.GLRMV3.GLRMParametersV3
user_y - Variable in class hex.schemas.GLRMV3.GLRMParametersV3

V

v_key - Variable in class hex.schemas.SVDModelV99.SVDModelOutputV99
validate(GLM) - Method in class hex.glm.GLMModel.GLMParameters
validateWithCheckpoint(SharedTreeModel.SharedTreeParameters) - Method in class hex.tree.SharedTreeModel.SharedTreeParameters: This method will take actual parameters and validate them with parameters of requested checkpoint.
validation_rows - Variable in class hex.deeplearning.DeepLearningModel
validDinfo(Frame) - Method in class hex.DataInfo
value() - Method in enum hex.tree.DHistogram.NASplitDir
valueOf(String) - Static method in enum hex.coxph.CoxPHModel.CoxPHParameters.CoxPHTies: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum hex.DataInfo.TransformType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum hex.deeplearning.DeepLearningModel.DeepLearningParameters.Activation: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum hex.deeplearning.DeepLearningModel.DeepLearningParameters.ClassSamplingMethod: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum hex.deeplearning.DeepLearningModel.DeepLearningParameters.InitialWeightDistribution: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum hex.deeplearning.DeepLearningModel.DeepLearningParameters.Loss: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum hex.deeplearning.DeepLearningModel.DeepLearningParameters.MissingValuesHandling: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum hex.deepwater.DeepWaterParameters.Activation: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum hex.deepwater.DeepWaterParameters.Backend: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum hex.deepwater.DeepWaterParameters.MissingValuesHandling: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum hex.deepwater.DeepWaterParameters.Network: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum hex.deepwater.DeepWaterParameters.ProblemType: 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.kmeans.KMeans.Initialization: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum hex.pca.PCAModel.PCAParameters.Method: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum hex.svd.SVDModel.SVDParameters.Method: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum hex.tree.DHistogram.NASplitDir: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum hex.tree.SharedTreeModel.SharedTreeParameters.HistogramType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum hex.word2vec.Word2Vec.NormModel: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum hex.word2vec.Word2Vec.WordModel: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum hex.word2vec.Word2VecModel.AggregateMethod: Returns the enum constant of this type with the specified name.
values() - Static method in enum hex.coxph.CoxPHModel.CoxPHParameters.CoxPHTies: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum hex.DataInfo.TransformType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum hex.deeplearning.DeepLearningModel.DeepLearningParameters.Activation: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum hex.deeplearning.DeepLearningModel.DeepLearningParameters.ClassSamplingMethod: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum hex.deeplearning.DeepLearningModel.DeepLearningParameters.InitialWeightDistribution: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum hex.deeplearning.DeepLearningModel.DeepLearningParameters.Loss: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum hex.deeplearning.DeepLearningModel.DeepLearningParameters.MissingValuesHandling: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum hex.deepwater.DeepWaterParameters.Activation: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum hex.deepwater.DeepWaterParameters.Backend: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum hex.deepwater.DeepWaterParameters.MissingValuesHandling: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum hex.deepwater.DeepWaterParameters.Network: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum hex.deepwater.DeepWaterParameters.ProblemType: 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.kmeans.KMeans.Initialization: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum hex.pca.PCAModel.PCAParameters.Method: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum hex.svd.SVDModel.SVDParameters.Method: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum hex.tree.DHistogram.NASplitDir: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum hex.tree.SharedTreeModel.SharedTreeParameters.HistogramType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum hex.word2vec.Word2Vec.NormModel: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum hex.word2vec.Word2Vec.WordModel: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum hex.word2vec.Word2VecModel.AggregateMethod: Returns an array containing the constants of this enum type, in the order they are declared.
var(int) - Method in class hex.tree.DHistogram: compute the sample variance within a given bin
variable_importances - Variable in class hex.schemas.DeepLearningV3.DeepLearningParametersV3: Whether to compute variable importances for input features.
variable_importances - Variable in class hex.schemas.DeepWaterV3.DeepWaterParametersV3: Whether to compute variable importances for input features.
variance(double) - Method in class hex.glm.GLMModel.GLMParameters
variance(double) - Method in class hex.glm.GLMModel.GLMWeightsFun
varImp() - Method in class hex.deeplearning.DeepLearningModel
vcov() - Method in class hex.glm.GLMModel.GLMOutput: Variance Covariance matrix accessor.
vec_nids(Frame, int) - Method in class hex.tree.SharedTree
vec_offset(Frame) - Method in class hex.tree.SharedTree
vec_oobt(Frame) - Method in class hex.tree.SharedTree
vec_resp(Frame) - Method in class hex.tree.SharedTree
vec_size - Variable in class hex.schemas.Word2VecV3.Word2VecParametersV3
vec_tree(Frame, int) - Method in class hex.tree.SharedTree
vec_weight(Frame) - Method in class hex.tree.SharedTree
vec_work(Frame, int) - Method in class hex.tree.SharedTree
vectors_frame - Variable in class hex.schemas.Word2VecTransformV3
visit() - Method in class hex.tree.TreeVisitor
votes() - Method in class hex.tree.drf.TreeMeasuresCollector.TreeVotes: Returns number of positive votes per tree.

W

w - Variable in class hex.glm.GLMModel.GLMWeights
W - Variable in class hex.schemas.GramV3
w(int) - Method in class hex.tree.DHistogram
water.api - package water.api
water.rapids.prims.word2vec - package water.rapids.prims.word2vec
weight - Variable in class hex.DataInfo.Row
weightChunkId() - Method in class hex.DataInfo
weightIndex - Variable in class hex.tree.SharedTree.FrameMap
weights_column - Variable in class hex.coxph.CoxPHModel.CoxPHParameters
window_size - Variable in class hex.schemas.Word2VecV3.Word2VecParametersV3
wNA() - Method in class hex.tree.DHistogram
word - Variable in class hex.schemas.Word2VecSynonymsV3
Word2Vec - Class in hex.word2vec
Word2Vec(boolean) - Constructor for class hex.word2vec.Word2Vec
Word2Vec(Word2VecModel.Word2VecParameters) - Constructor for class hex.word2vec.Word2Vec
Word2Vec.NormModel - Enum in hex.word2vec
Word2Vec.WordModel - Enum in hex.word2vec
Word2VecHandler - Class in hex.api
Word2VecHandler() - Constructor for class hex.api.Word2VecHandler
Word2VecModel - Class in hex.word2vec
Word2VecModel(Key<Word2VecModel>, Word2VecModel.Word2VecParameters, Word2VecModel.Word2VecOutput) - Constructor for class hex.word2vec.Word2VecModel
Word2VecModel.AggregateMethod - Enum in hex.word2vec
Word2VecModel.Vocabulary - Class in hex.word2vec
Word2VecModel.Word2VecModelInfo - Class in hex.word2vec
Word2VecModel.Word2VecModelInfo() - 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
Word2VecModel.WordCounts - Class in hex.word2vec
Word2VecModelV3 - Class in hex.schemas
Word2VecModelV3() - Constructor for class hex.schemas.Word2VecModelV3
Word2VecModelV3.Word2VecModelOutputV3 - Class in hex.schemas
Word2VecModelV3.Word2VecModelOutputV3() - Constructor for class hex.schemas.Word2VecModelV3.Word2VecModelOutputV3
Word2VecMojoWriter - Class in hex.word2vec: MOJO serializer for word2vec model.
Word2VecMojoWriter() - Constructor for class hex.word2vec.Word2VecMojoWriter
Word2VecMojoWriter(Word2VecModel) - Constructor for class hex.word2vec.Word2VecMojoWriter
Word2VecSynonymsV3 - Class in hex.schemas
Word2VecSynonymsV3() - Constructor for class hex.schemas.Word2VecSynonymsV3
Word2VecTransformV3 - Class in hex.schemas
Word2VecTransformV3() - Constructor for class hex.schemas.Word2VecTransformV3
Word2VecV3 - Class in hex.schemas
Word2VecV3() - Constructor for class hex.schemas.Word2VecV3
Word2VecV3.Word2VecParametersV3 - Class in hex.schemas
Word2VecV3.Word2VecParametersV3() - Constructor for class hex.schemas.Word2VecV3.Word2VecParametersV3
word_model - Variable in class hex.schemas.Word2VecV3.Word2VecParametersV3
WordCountTask - Class in hex.word2vec: Reduce a string column of a given Vec to a set of unique words and their frequency counts Currently the array is consolidated on the calling node.
words_frame - Variable in class hex.schemas.Word2VecTransformV3
WordVectorConverter - Class in hex.word2vec
WordVectorConverter(Job<Word2VecModel>, int, int) - Constructor for class hex.word2vec.WordVectorConverter
WordVectorTrainer - Class in hex.word2vec
WordVectorTrainer(Job<Word2VecModel>, Word2VecModel.Word2VecModelInfo) - Constructor for class hex.word2vec.WordVectorTrainer
work0Index - Variable in class hex.tree.SharedTree.FrameMap
WORK_TOTAL - Static variable in class hex.glm.GLM
write_impl(AutoBuffer) - Method in class hex.word2vec.WordCountTask
writeAll_impl(AutoBuffer) - Method in class hex.glrm.GLRMModel
writeAll_impl(AutoBuffer) - Method in class hex.StackedEnsembleModel: Write out models (base + metalearner)
writeAll_impl(AutoBuffer) - Method in class hex.svd.SVDModel: Write out K/V pairs
writeAll_impl(AutoBuffer) - Method in class hex.tree.SharedTreeModel: Write out K/V pairs
writeModelData() - Method in class hex.deepwater.DeepwaterMojoWriter
writeModelData() - Method in class hex.glm.GLMMojoWriter
writeModelData() - Method in class hex.glrm.GlrmMojoWriter
writeModelData() - Method in class hex.kmeans.KMeansMojoWriter
writeModelData() - Method in class hex.tree.drf.DrfMojoWriter
writeModelData() - Method in class hex.tree.gbm.GbmMojoWriter
writeModelData() - Method in class hex.tree.SharedTreeMojoWriter
writeModelData() - Method in class hex.word2vec.Word2VecMojoWriter
wsum() - Method in class hex.glm.GLMTask.YMUTask
wY(int) - Method in class hex.tree.DHistogram
wYNA() - Method in class hex.tree.DHistogram
wYY(int) - Method in class hex.tree.DHistogram
wYYNA() - Method in class hex.tree.DHistogram

X

X - Variable in class hex.schemas.GramV3

Z

z - Variable in class hex.glm.GLMModel.GLMWeights
zValues() - Method in class hex.glm.GLMModel.GLMOutput

_

_a - Variable in class hex.deeplearning.Neurons
_abAux - Variable in class hex.tree.DTree
_activation - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters: The activation function (non-linearity) to be used the neurons in the hidden layers.
_activation - Variable in class hex.deepwater.DeepWaterParameters: The activation function (non-linearity) to be used the neurons in the hidden layers.
_activeCols - Variable in class hex.DataInfo
_adaptedFrame - Variable in class hex.DataInfo
_adaptive_rate - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters: The implemented adaptive learning rate algorithm (ADADELTA) automatically combines the benefits of learning rate annealing and momentum training to avoid slow convergence.
_alpha - Variable in class hex.glm.GLMModel.GLMParameters
_apriori - Variable in class hex.naivebayes.NaiveBayesModel.NaiveBayesOutput
_apriori_raw - Variable in class hex.naivebayes.NaiveBayesModel.NaiveBayesOutput
_archetypes - Variable in class hex.glrm.GLRMModel.GLRMOutput
_archetypes_raw - Variable in class hex.glrm.GLRMModel.GLRMOutput
_atq - Variable in class hex.util.LinearAlgebraUtils.SMulTask
_autoencoder - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
_autoencoder - Variable in class hex.deepwater.DeepWaterParameters
_average_activation - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
_avg_a - Variable in class hex.deeplearning.Neurons
_avg_change_obj - Variable in class hex.glrm.GLRMModel.GLRMOutput
_b - Variable in class hex.deeplearning.Neurons
_backend - Variable in class hex.deepwater.DeepWaterParameters
_base_models - Variable in class hex.StackedEnsembleModel.StackedEnsembleParameters: Which models can we choose from?
_bEA - Variable in class hex.deeplearning.Neurons
_best_lambda_idx - Variable in class hex.glm.GLMModel.GLMOutput
_beta_constraints - Variable in class hex.glm.GLMModel.GLMParameters
_beta_epsilon - Variable in class hex.glm.GLMModel.GLMParameters
_betweenss - Variable in class hex.kmeans.KMeansModel.KMeansOutput
_bin - Variable in class hex.tree.DTree.Split
_binomial - Variable in class hex.glm.GLMModel.GLMOutput
_binomial_double_trees - Variable in class hex.tree.drf.DRFModel.DRFParameters
_build_tree_one_node - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters
_byte_size - Variable in class hex.tree.TreeStats
_cache_data - Variable in class hex.deepwater.DeepWaterParameters
_calib - Variable in class hex.tree.SharedTree
_calib_model - Variable in class hex.tree.SharedTreeModel.SharedTreeOutput
_calibrate_model - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters
_calibration_frame - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters
_catcnt - Variable in class hex.glrm.ModelMetricsGLRM
_catcnt - Variable in class hex.glrm.ModelMetricsGLRM.GlrmModelMetricsBuilder
_categorical_column_count - Variable in class hex.kmeans.KMeansModel.KMeansOutput
_caterr - Variable in class hex.glrm.ModelMetricsGLRM
_catLvls - Variable in class hex.DataInfo
_catMissing - Variable in class hex.DataInfo
_catOffsets - Variable in class hex.DataInfo
_catOffsets - Variable in class hex.glrm.GLRMModel.GLRMOutput
_catOffsets - Variable in class hex.pca.PCAModel.PCAOutput
_catOffsets - Variable in class hex.svd.SVDModel.SVDOutput
_cats - Variable in class hex.DataInfo
_channels - Variable in class hex.deepwater.DeepWaterParameters
_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.
_clip_gradient - Variable in class hex.deepwater.DeepWaterParameters
_coefficient_names - Variable in class hex.glm.GLMModel.RegularizationPath
_coefficients - Variable in class hex.glm.GLMModel.RegularizationPath
_coefficients_std - Variable in class hex.glm.GLMModel.RegularizationPath
_coefNames - Variable in class hex.DataInfo
_col - Variable in class hex.tree.DTree.Split
_col_major - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
_col_sample_rate - Variable in class hex.tree.gbm.GBMModel.GBMParameters
_col_sample_rate_change_per_level - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters
_col_sample_rate_per_tree - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters
_cols - Variable in class hex.tree.DTree
_compute_metrics - Variable in class hex.naivebayes.NaiveBayesModel.NaiveBayesParameters
_compute_metrics - Variable in class hex.pca.PCAModel.PCAParameters
_compute_p_values - Variable in class hex.glm.GLMModel.GLMParameters
_counts - Variable in class hex.aggregator.AggregatorModel
_ct - Variable in class hex.tree.TreeVisitor
_cv - Variable in class hex.glm.GLM
_d - Variable in class hex.svd.SVDModel.SVDOutput
_depth - Variable in class hex.tree.DTree
_depth - Variable in class hex.tree.TreeVisitor
_device_id - Variable in class hex.deepwater.DeepWaterParameters
_diag - Variable in class hex.gram.Gram
_diag - Variable in class hex.gram.Gram.Cholesky
_diagAdded - Variable in class hex.gram.Gram
_diagN - Variable in class hex.gram.Gram
_diagnostics - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters: Gather diagnostics for hidden layers, such as mean and RMS values of learning rate, momentum, weights and biases.
_dinfo - Variable in class hex.FrameTask
_dinfo - Variable in class hex.FrameTask2
_dinfo - Variable in class hex.gram.Gram.OuterGramTask
_dropout - Variable in class hex.deeplearning.Neurons: For Dropout training
_e - Variable in class hex.deeplearning.Neurons
_early_stopping - Variable in class hex.glm.GLMModel.GLMParameters
_eigenvectors - Variable in class hex.glrm.GLRMModel.GLRMOutput
_eigenvectors - Variable in class hex.pca.PCAModel.PCAOutput
_eigenvectors_raw - Variable in class hex.glrm.GLRMModel.GLRMOutput
_eigenvectors_raw - Variable in class hex.pca.PCAModel.PCAOutput
_elastic_averaging - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
_elastic_averaging_moving_rate - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
_elastic_averaging_regularization - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
_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.deepwater.DeepWaterParameters: The number of passes over the training dataset to be carried out.
_epochs - Variable in class hex.word2vec.Word2VecModel.Word2VecOutput
_epochs - Variable in class hex.word2vec.Word2VecModel.Word2VecParameters
_eps_prob - Variable in class hex.naivebayes.NaiveBayesModel.NaiveBayesParameters
_eps_sdev - Variable in class hex.naivebayes.NaiveBayesModel.NaiveBayesParameters
_epsilon - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters: The second of two hyper parameters for adaptive learning rate (ADADELTA).
_estimate_k - Variable in class hex.kmeans.KMeansModel.KMeansParameters
_exactLambdas - Variable in class hex.glm.GLMModel.GLMParameters
_exemplar_assignment_vec_key - Variable in class hex.aggregator.AggregatorModel
_exemplars - Variable in class hex.aggregator.AggregatorModel
_expand_user_y - Variable in class hex.glrm.GLRMModel.GLRMParameters
_explained_deviance_train - Variable in class hex.glm.GLMModel.RegularizationPath
_explained_deviance_valid - Variable in class hex.glm.GLMModel.RegularizationPath
_export_native_parameters_prefix - Variable in class hex.deepwater.DeepWaterParameters
_export_weights_and_biases - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
_family - Variable in class hex.glm.GLMModel.GLMParameters
_fast_mode - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters: Enable fast mode (minor approximation in back-propagation), should not affect results significantly.
_fold - Variable in class hex.DataInfo
_force_load_balance - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters: Increase training speed on small datasets by splitting it into many chunks to allow utilization of all cores.
_frame2DProduce - Variable in class hex.gram.Gram
_fullInfo - Variable in class hex.glm.ComputationState.GLMSubsetGinfo
_gamma_x - Variable in class hex.glrm.GLRMModel.GLRMParameters
_gamma_y - Variable in class hex.glrm.GLRMModel.GLRMParameters
_generatedWeights - Variable in class hex.glm.GLM
_globalQuantilesKey - Variable in class hex.tree.DHistogram
_gpu - Variable in class hex.deepwater.DeepWaterParameters
_gradient - Variable in class hex.optimization.OptimizationUtils.GradientInfo
_gradient_epsilon - Variable in class hex.glm.GLMModel.GLMParameters
_gram - Variable in class hex.glm.GLMTask.GLMIterationTask
_gram - Variable in class hex.glm.GLMTask.LSTask
_gram - Variable in class hex.gram.Gram.GramTask
_gram - Variable in class hex.gram.Gram.OuterGramTask
_hasQuantiles - Variable in class hex.tree.DHistogram
_hidden - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters: The number and size of each hidden layer in the model.
_hidden - Variable in class hex.deepwater.DeepWaterParameters: 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.
_hidden_dropout_ratios - Variable in class hex.deepwater.DeepWaterParameters: A fraction of the inputs for each hidden layer to be omitted from training in order to improve generalization.
_histogram_type - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters
_history_average_SEE - Variable in class hex.svd.SVDModel.SVDOutput
_history_eigenVectorIndex - Variable in class hex.svd.SVDModel.SVDOutput
_history_err - Variable in class hex.svd.SVDModel.SVDOutput
_history_objective - Variable in class hex.glrm.GLRMModel.GLRMOutput
_history_step_size - Variable in class hex.glrm.GLRMModel.GLRMOutput
_history_withinss - Variable in class hex.kmeans.KMeansModel.KMeansOutput
_histoType - Variable in class hex.tree.DHistogram
_hs - Variable in class hex.tree.DTree.UndecidedNode
_image_shape - Variable in class hex.deepwater.DeepWaterParameters
_importance - Variable in class hex.glrm.GLRMModel.GLRMOutput
_importance - Variable in class hex.pca.PCAModel.PCAOutput
_impute_missing - Variable in class hex.pca.PCAModel.PCAParameters
_impute_missing - Variable in class hex.svd.SVDModel.SVDParameters
_impute_original - Variable in class hex.glrm.GLRMModel.GLRMParameters
_impute_original - Variable in class hex.glrm.ModelMetricsGLRM.GlrmModelMetricsBuilder
_imputeMissing - Variable in class hex.DataInfo
_index - Variable in class hex.deeplearning.Neurons
_init - Variable in class hex.glrm.GLRMModel.GLRMParameters
_init - Variable in class hex.kmeans.KMeansModel.KMeansParameters
_init_f - Variable in class hex.tree.SharedTreeModel.SharedTreeOutput: InitF value (for zero trees) f0 = mean(yi) for gaussian f0 = log(yi/1-yi) for bernoulli For GBM bernoulli, the initial prediction for 0 trees is p = 1/(1+exp(-f0)) From this, the mse for 0 trees (null model) can be computed as follows: mean((yi-p)^2)
_init_key - Variable in class hex.glrm.GLRMModel.GLRMOutput
_init_learning_rate - Variable in class hex.word2vec.Word2VecModel.Word2VecParameters
_init_step_size - Variable in class hex.glrm.GLRMModel.GLRMParameters
_initial_biases - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters: Frame keys for initial bias vectors
_initial_score_interval - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters
_initial_weight_distribution - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters: The distribution from which initial weights are to be drawn.
_initial_weight_scale - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters: The scale of the distribution function for Uniform or Normal distributions.
_initial_weights - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters: Frame keys for initial weight matrices
_initialPrediction - Variable in class hex.tree.SharedTree
_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).
_input_dropout_ratio - Variable in class hex.deepwater.DeepWaterParameters: A fraction of the features for each training row to be omitted from training in order to improve generalization (dimension sampling).
_interactionColumns - Variable in class hex.DataInfo
_interactions - Variable in class hex.DataInfo
_interactions - Variable in class hex.glm.GLMModel.GLMParameters
_interactionVecs - Variable in class hex.DataInfo
_intercept - Variable in class hex.DataInfo
_intercept - Variable in class hex.glm.GLMModel.GLMParameters
_intLvls - Variable in class hex.DataInfo
_isInt - Variable in class hex.tree.DHistogram
_iterations - Variable in class hex.example.ExampleModel.ExampleOutput
_iterations - Variable in class hex.glrm.GLRMModel.GLRMOutput
_iterations - Variable in class hex.kmeans.KMeansModel.KMeansOutput
_iterations - Variable in class hex.svd.SVDModel.SVDOutput
_jobKey - Variable in class hex.FrameTask
_k - Variable in class hex.aggregator.AggregatorModel.AggregatorParameters
_k - Variable in class hex.glrm.GLRMModel.GLRMParameters
_k - Variable in class hex.kmeans.KMeansModel.KMeansOutput
_k - Variable in class hex.pca.PCAModel.PCAParameters
_keep_u - Variable in class hex.svd.SVDModel.SVDParameters
_l1 - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters: A regularization method that constrains the absolute value of the weights and has the net effect of dropping some weights (setting them to zero) from a model to reduce complexity and avoid overfitting.
_l2 - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters: A regularization method that constrains the sum of the squared weights.
_lambda - Variable in class hex.glm.GLMModel.GLMParameters
_lambda_1se - Variable in class hex.glm.GLMModel.GLMOutput
_lambda_max - Variable in class hex.glm.GLMModel
_lambda_min_ratio - Variable in class hex.glm.GLMModel.GLMParameters
_lambda_search - Variable in class hex.glm.GLMModel.GLMParameters
_lambdas - Variable in class hex.glm.GLMModel.RegularizationPath
_laplace - Variable in class hex.naivebayes.NaiveBayesModel.NaiveBayesParameters
_learn_rate - Variable in class hex.tree.gbm.GBMModel.GBMParameters
_learn_rate_annealing - Variable in class hex.tree.gbm.GBMModel.GBMParameters
_learning_rate - Variable in class hex.deepwater.DeepWaterParameters: 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.
_learning_rate_annealing - Variable in class hex.deepwater.DeepWaterParameters: Learning rate annealing reduces the learning rate to "freeze" into local minima in the optimization landscape.
_leaves - Variable in class hex.tree.DTree
_len - Variable in class hex.tree.DTree
_levels - Variable in class hex.naivebayes.NaiveBayesModel.NaiveBayesOutput
_likelihood - Variable in class hex.glm.GLMTask.GLMIterationTask
_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.glrm.GLRMModel.GLRMParameters
_loss_by_col - Variable in class hex.glrm.GLRMModel.GLRMParameters
_loss_by_col_idx - Variable in class hex.glrm.GLRMModel.GLRMParameters
_lossFunc - Variable in class hex.glrm.GLRMModel.GLRMOutput
_lsNeeded - Variable in class hex.glm.ComputationState
_matches - Variable in class hex.grep.GrepModel.GrepOutput
_max_abs_leafnode_pred - Variable in class hex.tree.gbm.GBMModel.GBMParameters
_max_active_predictors - Variable in class hex.glm.GLMModel.GLMParameters
_max_categorical_features - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters: Max.
_max_depth - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters
_max_depth - Variable in class hex.tree.TreeStats
_max_iterations - Variable in class hex.example.ExampleModel.ExampleParameters
_max_iterations - Variable in class hex.glm.GLMModel.GLMParameters
_max_iterations - Variable in class hex.glrm.GLRMModel.GLRMParameters
_max_iterations - Variable in class hex.kmeans.KMeansModel.KMeansParameters
_max_iterations - Variable in class hex.pca.PCAModel.PCAParameters
_max_iterations - Variable in class hex.svd.SVDModel.SVDParameters
_max_leaves - Variable in class hex.tree.TreeStats
_max_updates - Variable in class hex.glrm.GLRMModel.GLRMParameters
_max_w2 - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters: A maximum on the sum of the squared incoming weights into any one neuron.
_maxEx - Variable in class hex.tree.DHistogram
_maxIn - Variable in class hex.tree.DHistogram
_maxs - Variable in class hex.example.ExampleModel.ExampleOutput
_mean_depth - Variable in class hex.tree.TreeStats
_mean_image_file - Variable in class hex.deepwater.DeepWaterParameters
_mean_leaves - Variable in class hex.tree.TreeStats
_metalearner - Variable in class hex.StackedEnsembleModel.StackedEnsembleOutput
_min - Variable in class hex.tree.DHistogram
_min2 - Variable in class hex.tree.DHistogram
_min_depth - Variable in class hex.tree.TreeStats
_min_leaves - Variable in class hex.tree.TreeStats
_min_prob - Variable in class hex.naivebayes.NaiveBayesModel.NaiveBayesParameters
_min_rows - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters
_min_sdev - Variable in class hex.naivebayes.NaiveBayesModel.NaiveBayesParameters
_min_split_improvement - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters
_min_step_size - Variable in class hex.glrm.GLRMModel.GLRMParameters
_min_word_freq - Variable in class hex.word2vec.Word2VecModel.Word2VecParameters
_mini_batch_size - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
_mini_batch_size - Variable in class hex.deepwater.DeepWaterParameters
_minSplitImprovement - Variable in class hex.tree.DHistogram
_miscls - Variable in class hex.glrm.ModelMetricsGLRM.GlrmModelMetricsBuilder
_missing_values_handling - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
_missing_values_handling - Variable in class hex.deepwater.DeepWaterParameters
_missing_values_handling - Variable in class hex.glm.GLMModel.GLMParameters
_model - Variable in class hex.ensemble.StackedEnsemble
_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_ramp - Variable in class hex.deepwater.DeepWaterParameters: 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_stable - Variable in class hex.deepwater.DeepWaterParameters: 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.
_momentum_start - Variable in class hex.deepwater.DeepWaterParameters: The momentum_start parameter controls the amount of momentum at the beginning of training.
_mtries - Variable in class hex.tree.drf.DRFModel.DRFParameters
_mtry - Variable in class hex.tree.SharedTree
_mtry_per_tree - Variable in class hex.tree.SharedTree
_mtrys - Variable in class hex.tree.DTree
_mtrys_per_tree - Variable in class hex.tree.DTree
_multi_loss - Variable in class hex.glrm.GLRMModel.GLRMParameters
_multinomial - Variable in class hex.glm.GLMModel.GLMOutput
_name - Variable in class hex.tree.DHistogram
_names_expanded - Variable in class hex.glrm.GLRMModel.GLRMOutput
_names_expanded - Variable in class hex.svd.SVDModel.SVDOutput
_nbin - Variable in class hex.tree.DHistogram
_nbins - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters
_nbins_cats - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters
_nbins_top_level - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters
_ncats - Variable in class hex.glrm.GLRMModel.GLRMOutput
_ncats - Variable in class hex.naivebayes.NaiveBayesModel.NaiveBayesOutput
_ncats - Variable in class hex.pca.PCAModel.PCAOutput
_ncats - Variable in class hex.svd.SVDModel.SVDOutput
_nclass - Variable in class hex.tree.DTreeScorer
_ncols - Variable in class hex.tree.DTreeScorer
_ncols - Variable in class hex.tree.SharedTree
_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.
_network - Variable in class hex.deepwater.DeepWaterParameters
_network_definition_file - Variable in class hex.deepwater.DeepWaterParameters
_network_parameters_file - Variable in class hex.deepwater.DeepWaterParameters
_nid - Variable in class hex.tree.DTree.Node
_nids - Variable in class hex.tree.DTree.DecidedNode
_nlambdas - Variable in class hex.glm.GLMModel.GLMParameters
_nnums - Variable in class hex.glrm.GLRMModel.GLRMOutput
_nnums - Variable in class hex.pca.PCAModel.PCAOutput
_nnums - Variable in class hex.svd.SVDModel.SVDOutput
_nobs - Variable in class hex.glm.GLMModel
_nobs - Variable in class hex.glrm.GLRMModel.GLRMOutput
_nobs - Variable in class hex.gram.Gram.GramTask
_nobs - Variable in class hex.gram.Gram.OuterGramTask
_nobs - Variable in class hex.pca.PCAModel.PCAOutput
_nobs - Variable in class hex.svd.SVDModel.SVDOutput
_nodes - Variable in class hex.tree.TreeVisitor
_non_negative - Variable in class hex.glm.GLMModel.GLMParameters
_norm_model - Variable in class hex.word2vec.Word2VecModel.Word2VecParameters
_normMul - Variable in class hex.DataInfo
_normMul - Variable in class hex.glrm.GLRMModel.GLRMOutput
_normMul - Variable in class hex.pca.PCAModel.PCAOutput
_normMul - Variable in class hex.svd.SVDModel.SVDOutput
_normMulnew - Variable in class hex.glm.GLMTask.GLMCoordinateDescentTaskSeqNaive
_normMulold - Variable in class hex.glm.GLMTask.GLMCoordinateDescentTaskSeqNaive
_normRespMul - Variable in class hex.DataInfo
_normRespSub - Variable in class hex.DataInfo
_normSub - Variable in class hex.DataInfo
_normSub - Variable in class hex.glrm.GLRMModel.GLRMOutput
_normSub - Variable in class hex.pca.PCAModel.PCAOutput
_normSub - Variable in class hex.svd.SVDModel.SVDOutput
_normSubnew - Variable in class hex.glm.GLMTask.GLMCoordinateDescentTaskSeqNaive
_normSubold - Variable in class hex.glm.GLMTask.GLMCoordinateDescentTaskSeqNaive
_nrows - Variable in class hex.DataInfo.Rows
_nrows - Variable in class hex.tree.drf.TreeMeasuresCollector.TreeMeasures: Number of processed row per tree.
_ntrees - Variable in class hex.tree.drf.TreeMeasuresCollector.TreeMeasures: Actual number of trees which votes are stored in this object
_ntrees - Variable in class hex.tree.SharedTree
_ntrees - Variable in class hex.tree.SharedTreeModel.SharedTreeOutput: Number of trees actually in the model (as opposed to requested)
_ntrees - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters
_nullDOF - Variable in class hex.glm.GLMModel
_num_trees - Variable in class hex.tree.TreeStats
_numcnt - Variable in class hex.glrm.ModelMetricsGLRM
_numcnt - Variable in class hex.glrm.ModelMetricsGLRM.GlrmModelMetricsBuilder
_numerr - Variable in class hex.glrm.ModelMetricsGLRM
_numMeans - Variable in class hex.DataInfo
_numOffsets - Variable in class hex.DataInfo
_nums - Variable in class hex.DataInfo
_nv - Variable in class hex.svd.SVDModel.SVDParameters
_obj_reg - Variable in class hex.glm.GLMModel.GLMParameters
_objective - Variable in class hex.glrm.GLRMModel.GLRMOutput
_objective - Variable in class hex.pca.PCAModel.PCAOutput
_objective_epsilon - Variable in class hex.glm.GLMModel.GLMParameters
_objVal - Variable in class hex.optimization.OptimizationUtils.GradientInfo
_offset - Variable in class hex.DataInfo
_offsets - Variable in class hex.grep.GrepModel.GrepOutput
_only_v - Variable in class hex.svd.SVDModel.SVDParameters
_OOBEnabled - Variable in class hex.tree.ReconstructTreeState
_origa - Variable in class hex.deeplearning.Neurons: Layer state (one per neuron): activity, error
_outpus - Variable in class hex.DataInfo
_output_frame - Variable in class hex.aggregator.AggregatorModel.AggregatorOutput
_overwrite_with_best_model - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters: If enabled, store the best model under the destination key of this model at the end of training.
_overwrite_with_best_model - Variable in class hex.deepwater.DeepWaterParameters: If enabled, store the best model under the destination key of this model at the end of training.
_parms - Variable in class hex.tree.DTree
_pca_method - Variable in class hex.aggregator.AggregatorModel.AggregatorParameters
_pca_method - Variable in class hex.pca.PCAModel.PCAParameters
_pcond - Variable in class hex.naivebayes.NaiveBayesModel.NaiveBayesOutput
_pcond_raw - Variable in class hex.naivebayes.NaiveBayesModel.NaiveBayesOutput
_period - Variable in class hex.glrm.GLRMModel.GLRMParameters
_permutation - Variable in class hex.DataInfo
_permutation - Variable in class hex.glrm.GLRMModel.GLRMOutput
_permutation - Variable in class hex.glrm.ModelMetricsGLRM.GlrmModelMetricsBuilder
_permutation - Variable in class hex.pca.PCAModel.PCAOutput
_permutation - Variable in class hex.svd.SVDModel.SVDOutput
_pid - Variable in class hex.tree.DTree.Node
_pm - Variable in class hex.optimization.ADMM.L1Solver
_pre_trained - Variable in class hex.word2vec.Word2VecModel.Word2VecParameters
_pred - Variable in class hex.tree.DTree.LeafNode
_pred_indicator - Variable in class hex.kmeans.KMeansModel.KMeansParameters
_pred_noise_bandwidth - Variable in class hex.tree.gbm.GBMModel.GBMParameters
_predictor_transform - Variable in class hex.DataInfo
_previous - Variable in class hex.deeplearning.Neurons: References for feed-forward connectivity
_prior - Variable in class hex.glm.GLMModel.GLMParameters
_problem_type - Variable in class hex.deepwater.DeepWaterParameters
_quiet_mode - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters: Enable quiet mode for less output to standard output.
_quiet_mode - Variable in class hex.deepwater.DeepWaterParameters: Enable quiet mode for less output to standard output.
_r2_stopping - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters
_rand - Variable in class hex.tree.DTree
_rand - Variable in class hex.tree.SharedTree
_rate - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters: When adaptive learning rate is disabled, the magnitude of the weight updates are determined by the user specified learning rate (potentially annealed), and are a function of the difference between the predicted value and the target value.
_rate - Variable in class hex.tree.ReconstructTreeState
_rate_annealing - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters: Learning rate annealing reduces the learning rate to "freeze" into local minima in the optimization landscape.
_rate_decay - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters: The learning rate decay parameter controls the change of learning rate across layers.
_reassigned_count - Variable in class hex.kmeans.KMeansModel.KMeansOutput
_recover_svd - Variable in class hex.glrm.GLRMModel.GLRMParameters
_regex - Variable in class hex.grep.GrepModel.GrepParameters
_regression_stop - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters: The stopping criteria in terms of regression error (MSE) on the training data scoring dataset.
_regularization_x - Variable in class hex.glrm.GLRMModel.GLRMParameters
_regularization_y - Variable in class hex.glrm.GLRMModel.GLRMParameters
_rel_tol_num_exemplars - Variable in class hex.aggregator.AggregatorModel.AggregatorParameters
_remove_collinear_columns - Variable in class hex.glm.GLMModel.GLMParameters
_replicate_training_data - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters: Replicate the entire training dataset onto every node for faster training on small datasets.
_replicate_training_data - Variable in class hex.deepwater.DeepWaterParameters: Replicate the entire training dataset onto every node for faster training on small datasets.
_representation_key - Variable in class hex.glrm.GLRMModel.GLRMOutput
_representation_name - Variable in class hex.glrm.GLRMModel.GLRMOutput
_representation_name - Variable in class hex.glrm.GLRMModel.GLRMParameters
_reproducible - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters: Force reproducibility on small data (will be slow - only uses 1 thread)
_rescnt - Variable in class hex.naivebayes.NaiveBayesModel.NaiveBayesOutput
_response_transform - Variable in class hex.DataInfo
_responses - Variable in class hex.DataInfo
_rho - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters: The first of two hyper parameters for adaptive learning rate (ADADELTA).
_row - Variable in class hex.FrameTask.ExtractDenseRow
_sample_rate - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters
_sample_rate_per_class - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters
_save_v_frame - Variable in class hex.svd.SVDModel.SVDParameters
_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_duty_cycle - Variable in class hex.deepwater.DeepWaterParameters: 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_interval - Variable in class hex.deepwater.DeepWaterParameters: The minimum time (in seconds) to elapse between model scoring.
_score_interval - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters
_score_training_samples - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters: The number of training dataset points to be used for scoring.
_score_training_samples - Variable in class hex.deepwater.DeepWaterParameters: The number of training dataset points to be used for scoring.
_score_tree_interval - Variable in class hex.tree.SharedTreeModel.SharedTreeParameters
_score_validation_samples - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters: The number of validation dataset points to be used for scoring.
_score_validation_samples - Variable in class hex.deepwater.DeepWaterParameters: The number of validation dataset points to be used for scoring.
_score_validation_sampling - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters: Method used to sample the validation dataset for scoring, see Score Validation Samples above.
_scoreCols - Variable in class hex.tree.DTree.UndecidedNode
_scored_train - Variable in class hex.tree.SharedTreeModel.SharedTreeOutput
_scored_valid - Variable in class hex.tree.SharedTreeModel.SharedTreeOutput
_seed - Variable in class hex.tree.DHistogram
_selected_lambda_idx - Variable in class hex.glm.GLMModel.GLMOutput
_sent_sample_rate - 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).
_shuffle_training_data - Variable in class hex.deepwater.DeepWaterParameters: 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.
_single_node_mode - Variable in class hex.deepwater.DeepWaterParameters: Run on a single node for fine-tuning of model parameters.
_singular_vals - Variable in class hex.glrm.GLRMModel.GLRMOutput
_skip - Variable in class hex.tree.DTreeScorer
_skipMissing - Variable in class hex.DataInfo
_solver - Variable in class hex.glm.GLMModel.GLMParameters
_sparse - Variable in class hex.DataInfo.Rows
_sparse - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
_sparse - Variable in class hex.deepwater.DeepWaterParameters
_sparse - Variable in class hex.FrameTask
_sparse - Variable in class hex.FrameTask2
_sparsity_beta - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
_splat - Variable in class hex.tree.DTree.DecidedNode
_split - Variable in class hex.tree.DTree.DecidedNode
_splitPts - Variable in class hex.tree.DHistogram
_sse - Variable in class hex.util.LinearAlgebraUtils.ForwardSolve
_st - Variable in class hex.tree.DTreeScorer
_standardize - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters: If enabled, automatically standardize the data.
_standardize - Variable in class hex.deepwater.DeepWaterParameters: If enabled, automatically standardize the data.
_standardize - Variable in class hex.glm.GLMModel.GLMParameters
_standardize - Variable in class hex.kmeans.KMeansModel.KMeansParameters
_std_deviation - Variable in class hex.glrm.GLRMModel.GLRMOutput
_std_deviation - Variable in class hex.pca.PCAModel.PCAOutput
_stdOverride - Variable in class hex.glm.GLMModel.GLMParameters
_step - Variable in class hex.tree.DHistogram
_step_size - Variable in class hex.glrm.GLRMModel.GLRMOutput
_svd_method - Variable in class hex.glrm.GLRMModel.GLRMParameters
_svd_method - Variable in class hex.svd.SVDModel.SVDParameters
_target_num_exemplars - Variable in class hex.aggregator.AggregatorModel.AggregatorParameters
_target_ratio_comm_to_comp - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
_target_ratio_comm_to_comp - Variable in class hex.deepwater.DeepWaterParameters
_temp - Variable in class hex.glm.GLMTask.GLMCoordinateDescentTaskSeqIntercept
_temp - Variable in class hex.glm.GLMTask.GLMCoordinateDescentTaskSeqNaive
_timeLastIterationEnter - Variable in class hex.deeplearning.DeepLearningModel
_timeLastScoreStart - Variable in class hex.deeplearning.DeepLearningModel
_tot_withinss - Variable in class hex.kmeans.KMeansModel.KMeansOutput
_total_variance - Variable in class hex.glrm.GLRMModel.GLRMOutput
_total_variance - Variable in class hex.pca.PCAModel.PCAOutput
_total_variance - Variable in class hex.svd.SVDModel.SVDOutput
_totss - Variable in class hex.kmeans.KMeansModel.KMeansOutput
_train_samples_per_iteration - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters: The number of training data rows to be processed per iteration.
_train_samples_per_iteration - Variable in class hex.deepwater.DeepWaterParameters: The number of training data rows to be processed per iteration.
_training_time_ms - Variable in class hex.glrm.GLRMModel.GLRMOutput
_training_time_ms - Variable in class hex.kmeans.KMeansModel.KMeansOutput
_training_time_ms - Variable in class hex.pca.PCAModel.PCAOutput
_training_time_ms - Variable in class hex.svd.SVDModel.SVDOutput
_training_time_ms - Variable in class hex.tree.SharedTreeModel.SharedTreeOutput: Training time
_transform - Variable in class hex.aggregator.AggregatorModel.AggregatorParameters
_transform - Variable in class hex.glrm.GLRMModel.GLRMParameters
_transform - Variable in class hex.pca.PCAModel.PCAParameters
_transform - Variable in class hex.svd.SVDModel.SVDParameters
_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 separately in the DKV.
_treeKeysAux - Variable in class hex.tree.SharedTreeModel.SharedTreeOutput
_trees - Variable in class hex.tree.DTreeScorer
_treeStats - Variable in class hex.tree.SharedTreeModel.SharedTreeOutput: More indepth tree stats
_tweedie_link_power - Variable in class hex.glm.GLMModel.GLMParameters
_tweedie_variance_power - Variable in class hex.glm.GLMModel.GLMParameters
_u - Variable in class hex.optimization.ADMM.L1Solver
_u_key - Variable in class hex.svd.SVDModel.SVDOutput
_u_name - Variable in class hex.svd.SVDModel.SVDParameters
_updates - Variable in class hex.glrm.GLRMModel.GLRMOutput
_use_all_factor_levels - Variable in class hex.aggregator.AggregatorModel.AggregatorParameters
_use_all_factor_levels - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters
_use_all_factor_levels - Variable in class hex.deepwater.DeepWaterParameters
_use_all_factor_levels - Variable in class hex.glm.GLMModel.GLMParameters
_use_all_factor_levels - Variable in class hex.pca.PCAModel.PCAParameters
_use_all_factor_levels - Variable in class hex.svd.SVDModel.SVDParameters
_useAllFactorLevels - Variable in class hex.DataInfo
_useFraction - Variable in class hex.FrameTask
_user_points - Variable in class hex.kmeans.KMeansModel.KMeansParameters
_user_x - Variable in class hex.glrm.GLRMModel.GLRMParameters
_user_y - Variable in class hex.glrm.GLRMModel.GLRMParameters
_v - Variable in class hex.svd.SVDModel.SVDOutput
_v_key - Variable in class hex.svd.SVDModel.SVDOutput
_v_name - Variable in class hex.svd.SVDModel.SVDParameters
_valid - Variable in class hex.DataInfo
_vals - Variable in class hex.tree.DHistogram
_variable_importances - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningModelOutput
_variable_importances - Variable in class hex.deeplearning.DeepLearningModel.DeepLearningParameters: Whether to compute variable importances for input features.
_variable_importances - Variable in class hex.deepwater.DeepWaterModelOutput
_variable_importances - Variable in class hex.tree.SharedTreeModel.SharedTreeOutput: Variable importances computed during training
_varimp - Variable in class hex.tree.SharedTreeModel.SharedTreeOutput
_vec_size - Variable in class hex.word2vec.Word2VecModel.Word2VecParameters
_vecs - Variable in class hex.word2vec.Word2VecModel.Word2VecOutput
_vecSize - Variable in class hex.word2vec.Word2VecModel.Word2VecOutput
_verbose - Variable in class hex.glrm.GLRMModel.GLRMParameters
_vocab - Variable in class hex.word2vec.Word2VecModel.Word2VecOutput
_w - Variable in class hex.deeplearning.Neurons
_wEA - Variable in class hex.deeplearning.Neurons
_weights - Variable in class hex.DataInfo
_window_size - Variable in class hex.word2vec.Word2VecModel.Word2VecParameters
_withinss - Variable in class hex.kmeans.KMeansModel.KMeansOutput
_word_model - Variable in class hex.word2vec.Word2VecModel.Word2VecParameters
_words - Variable in class hex.word2vec.Word2VecModel.Word2VecOutput
_xx - Variable in class hex.gram.Gram
_xx - Variable in class hex.gram.Gram.Cholesky
_xy - Variable in class hex.glm.GLMTask.LSTask
_ymu - Variable in class hex.glm.GLMModel
_ySigma - Variable in class hex.glm.GLMModel

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