- a -
- A() : AlphaDropout< InputDataType, OutputDataType >, LogCoshLoss< InputDataType, OutputDataType >
- AbsErrorVisitor() : AbsErrorVisitor
- AbsoluteError() : KDE< KernelType, MetricType, MatType, TreeType, DualTreeTraversalType, SingleTreeTraversalType >, KDEModel
- AccumAlpha() : KDEStat
- AccumError() : KDEStat
- Acrobot() : Acrobot
- Action() : ContinuousActionEnv::Action, Pendulum::Action, QLearning< EnvironmentType, NetworkType, UpdaterType, PolicyType, ReplayType >, SAC< EnvironmentType, QNetworkType, PolicyNetworkType, UpdaterType, ReplayType >
- ActiveSet() : LARS
- AdaBoost() : AdaBoost< WeakLearnerType, MatType >
- AdaBoostModel() : AdaBoostModel
- AdaptiveMaxPooling() : AdaptiveMaxPooling< InputDataType, OutputDataType >
- AdaptiveMeanPooling() : AdaptiveMeanPooling< InputDataType, OutputDataType >
- Add() : Add< InputDataType, OutputDataType >, AddMerge< InputDataType, OutputDataType, CustomLayers >, BRNN< OutputLayerType, MergeLayerType, MergeOutputType, InitializationRuleType, CustomLayers >, Concat< InputDataType, OutputDataType, CustomLayers >, FFN< OutputLayerType, InitializationRuleType, CustomLayers >, Highway< InputDataType, OutputDataType, CustomLayers >, MultiplyMerge< InputDataType, OutputDataType, CustomLayers >, RNN< OutputLayerType, InitializationRuleType, CustomLayers >, Sequential< InputDataType, OutputDataType, Residual, CustomLayers >, VRClassReward< InputDataType, OutputDataType >, IO
- AddMerge() : AddMerge< InputDataType, OutputDataType, CustomLayers >
- AddTask() : AddTask
- AddToken() : StringEncodingDictionary< Token >, StringEncodingDictionary< boost::string_view >, StringEncodingDictionary< int >
- AddVisitor() : AddVisitor< CustomLayers >
- AggregatedPolicy() : AggregatedPolicy< PolicyType >
- Aliases() : IO
- AllDimensionSelect() : AllDimensionSelect
- AllowEmptyClusters() : AllowEmptyClusters
- Alpha() : AdaBoost< WeakLearnerType, MatType >, CELU< InputDataType, OutputDataType >, ELU< InputDataType, OutputDataType >, FlexibleReLU< InputDataType, OutputDataType >, LeakyReLU< InputDataType, OutputDataType >, PReLU< InputDataType, OutputDataType >, BiasSVDPolicy, SVDPlusPlusPolicy, GammaDistribution, RAModel< SortPolicy >, RASearch< SortPolicy, MetricType, MatType, TreeType >, BayesianLinearRegression
- AlphaDash() : AlphaDropout< InputDataType, OutputDataType >
- AlphaDropout() : AlphaDropout< InputDataType, OutputDataType >
- AlphaUpper() : DTree< MatType, TagType >
- AMF() : AMF< TerminationPolicyType, InitializationRuleType, UpdateRuleType >
- Angle() : CartPole::State, ContinuousDoublePoleCart::State, DoublePoleCart::State
- AngleNormalize() : Pendulum
- Angles() : Radical
- AngularVelocity() : CartPole::State, ContinuousDoublePoleCart::State, DoublePoleCart::State, Pendulum::State
- AngularVelocity1() : Acrobot::State
- AngularVelocity2() : Acrobot::State
- Anneal() : AggregatedPolicy< PolicyType >, GreedyPolicy< EnvironmentType >
- Apply() : InitHMMModel, AMF< TerminationPolicyType, InitializationRuleType, UpdateRuleType >, BatchSVDPolicy, BiasSVDPolicy, NMFPolicy, RandomizedSVDPolicy, RegSVDPolicy, SVDCompletePolicy, SVDIncompletePolicy, SVDPlusPlusPolicy, SVDWrapper< Factorizer >, NystroemMethod< KernelType, PointSelectionPolicy >, KernelPCA< KernelType, KernelRule >, ExactSVDPolicy, PCA< DecompositionPolicy >, QUICSVDPolicy, RandomizedBlockKrylovSVDPolicy, RandomizedSVDPolicy, BiasSVD< OptimizerType >, RandomizedBlockKrylovSVD, RandomizedSVD, RegularizedSVD< OptimizerType >, SVDPlusPlus< OptimizerType >, TrainHMMModel
- ApplyConstraint() : DiagonalConstraint, EigenvalueRatioConstraint, NoConstraint, PositiveDefiniteConstraint
- ApplyKernelMatrix() : NaiveKernelRule< KernelType >, NystroemKernelRule< KernelType, PointSelectionPolicy >
- ApplyNormalizer() : KernelNormalizer
- Assert() : Log
- AssertDataConsistency() : CVBase< MLAlgorithm, MatType, PredictionsType, WeightsType >
- AssertWeightsConsistency() : CVBase< MLAlgorithm, MatType, PredictionsType, WeightsType >
- AssignToLeftNode() : MeanSplit< BoundType, MatType >, MidpointSplit< BoundType, MatType >, RPTreeMaxSplit< BoundType, MatType >, RPTreeMeanSplit< BoundType, MatType >, VantagePointSplit< BoundType, MatType, MaxNumSamples >
- AsyncLearning() : AsyncLearning< WorkerType, EnvironmentType, NetworkType, UpdaterType, PolicyType >
- Atoms() : LocalCoordinateCoding, SparseCoding
- AtomSize() : TrainingConfig
- AtrousConvolution() : AtrousConvolution< ForwardConvolutionRule, BackwardConvolutionRule, GradientConvolutionRule, InputDataType, OutputDataType >
- AttentionMask() : MultiheadAttention< InputDataType, OutputDataType, RegularizerType >
- AuxBound() : NeighborSearchStat< SortPolicy >
- AuxiliaryInfo() : RectangleTree< MetricType, StatisticType, MatType, SplitType, DescentType, AuxiliaryInformationType >
- Average() : BatchNorm< InputDataType, OutputDataType >
- AverageInitialization() : AverageInitialization
- AverageInterpolation() : AverageInterpolation
- AxisParallelProjVector() : AxisParallelProjVector