- s -

• SAC() : SAC< EnvironmentType, QNetworkType, PolicyNetworkType, UpdaterType, ReplayType >
• Sample() : BernoulliDistribution< DataType > , Acrobot , ContinuousDoublePoleCart , MountainCar , ContinuousDoublePoleCart , Pendulum , Acrobot , ContinuousMountainCar , RewardClipping< EnvironmentType > , ContinuousMountainCar , AggregatedPolicy< PolicyType > , GreedyPolicy< EnvironmentType > , NormalDistribution< DataType > , CartPole , DoublePoleCart , PrioritizedReplay< EnvironmentType > , RandomReplay< EnvironmentType > , DoublePoleCart , CartPole , DiscreteActionEnv , ContinuousActionEnv
• SampleAtLeaves() : RAModel< SortPolicy > , RASearch< SortPolicy, MetricType, MatType, TreeType >
• SampleHidden() : RBM< InitializationRuleType, DataType, PolicyType >
• SampleInitialization() : SampleInitialization
• SampleProportional() : PrioritizedReplay< EnvironmentType >
• SampleSlab() : RBM< InitializationRuleType, DataType, PolicyType >
• SampleSpike() : RBM< InitializationRuleType, DataType, PolicyType >
• SamplesScore() : SilhouetteScore
• SampleVisible() : RBM< InitializationRuleType, DataType, PolicyType >
• Samplings() : RefinedStart
• save() : HMM< Distribution >
• SaveOutputParameterVisitor() : SaveOutputParameterVisitor
• Scalar() : MultiplyConstant< InputDataType, OutputDataType >
• Scale() : MaxAbsScaler , MeanNormalization , MinMaxScaler , LaplaceDistribution , HyperbolicTangentKernel , ColumnsToBlocks , CoverTree< MetricType, StatisticType, MatType, RootPointPolicy > , Glimpse< InputDataType, OutputDataType > , VRClassReward< InputDataType, OutputDataType >
• ScaleData() : PCA< DecompositionPolicy >
• ScaleMax() : MinMaxScaler
• ScaleMin() : MinMaxScaler
• ScalerType() : ScalingModel
• ScalingModel() : ScalingModel
• Score() : DTBRules< MetricType, TreeType > , FastMKSRules< KernelType, TreeType > , KDERules< MetricType, KernelType, TreeType > , KDECleanRules< TreeType > , DualTreeKMeansRules< MetricType, TreeType > , PellegMooreKMeansRules< MetricType, TreeType > , NeighborSearchRules< SortPolicy, MetricType, TreeType > , RangeSearchRules< MetricType, TreeType > , RASearchRules< SortPolicy, MetricType, TreeType >
• Scores() : DTBRules< MetricType, TreeType > , FastMKSRules< KernelType, TreeType > , KDERules< MetricType, KernelType, TreeType > , DualTreeKMeansRules< MetricType, TreeType > , NeighborSearch< SortPolicy, MetricType, MatType, TreeType, DualTreeTraversalType, SingleTreeTraversalType > , NeighborSearchRules< SortPolicy, MetricType, TreeType > , RangeSearch< MetricType, MatType, TreeType > , RangeSearchRules< MetricType, TreeType >
• Sdp() : MatrixCompletion
• Search() : DrusillaSelect< MatType > , QDAFN< MatType > , CosineSearch , LMetricSearch< TPower > , PearsonSearch , FastMKS< KernelType, MatType, TreeType > , FastMKSModel , LSHSearch< SortPolicy, MatType > , NeighborSearch< SortPolicy, MetricType, MatType, TreeType, DualTreeTraversalType, SingleTreeTraversalType > , NSModel< SortPolicy > , RangeSearch< MetricType, MatType, TreeType > , RSModel , RAModel< SortPolicy > , RASearch< SortPolicy, MetricType, MatType, TreeType >
• SearchMode() : NeighborSearch< SortPolicy, MetricType, MatType, TreeType, DualTreeTraversalType, SingleTreeTraversalType > , NSModel< SortPolicy >
• SecondBound() : NeighborSearchStat< SortPolicy >
• SecondHashTable() : LSHSearch< SortPolicy, MatType >
• SecondHashWeights() : LSHSearch< SortPolicy, MatType >
• SeeAlso() : SeeAlso
• SeeAlsoWrapper() : SeeAlsoWrapper
• Select() : Select< InputDataType, OutputDataType > , OrderedPointSelection , RandomPointSelection , KMeansSelection< ClusteringType, maxIterations > , OrderedSelection , RandomSelection
• SelectAction() : QLearning< EnvironmentType, NetworkType, UpdaterType, PolicyType, ReplayType > , SAC< EnvironmentType, QNetworkType, PolicyNetworkType, UpdaterType, ReplayType >
• SelfKernel() : FastMKSStat
• Sequential() : Sequential< InputDataType, OutputDataType, residual, CustomLayers >
• serialize() : MaxPooling< InputDataType, OutputDataType > , MeanPooling< InputDataType, OutputDataType > , MiniBatchDiscrimination< InputDataType, OutputDataType > , MultiheadAttention< InputDataType, OutputDataType, RegularizerType > , MultiplyConstant< InputDataType, OutputDataType > , MultiplyMerge< InputDataType, OutputDataType, CustomLayers > , NoisyLinear< InputDataType, OutputDataType > , Padding< InputDataType, OutputDataType > , PReLU< InputDataType, OutputDataType > , PositionalEncoding< InputDataType, OutputDataType > , RBF< InputDataType, OutputDataType, Activation > , Recurrent< InputDataType, OutputDataType, CustomLayers > , RecurrentAttention< InputDataType, OutputDataType > , ReinforceNormal< InputDataType, OutputDataType > , Reparametrization< InputDataType, OutputDataType > , Select< InputDataType, OutputDataType > , Sequential< InputDataType, OutputDataType, residual, CustomLayers > , Softmax< InputDataType, OutputDataType > , Softmin< InputDataType, OutputDataType > , SoftShrink< InputDataType, OutputDataType > , SpatialDropout< InputDataType, OutputDataType > , Subview< InputDataType, OutputDataType > , TransposedConvolution< ForwardConvolutionRule, BackwardConvolutionRule, GradientConvolutionRule, InputDataType, OutputDataType > , VirtualBatchNorm< InputDataType, OutputDataType > , VRClassReward< InputDataType, OutputDataType > , WeightNorm< InputDataType, OutputDataType, CustomLayers > , CosineEmbeddingLoss< InputDataType, OutputDataType > , CrossEntropyError< InputDataType, OutputDataType > , DiceLoss< InputDataType, OutputDataType > , EarthMoverDistance< InputDataType, OutputDataType > , HingeEmbeddingLoss< InputDataType, OutputDataType > , HuberLoss< InputDataType, OutputDataType > , KLDivergence< InputDataType, OutputDataType > , L1Loss< InputDataType, OutputDataType > , LogCoshLoss< InputDataType, OutputDataType > , MarginRankingLoss< InputDataType, OutputDataType > , MeanAbsolutePercentageError< InputDataType, OutputDataType > , MeanBiasError< InputDataType, OutputDataType > , MeanSquaredError< InputDataType, OutputDataType > , MeanSquaredLogarithmicError< InputDataType, OutputDataType > , NegativeLogLikelihood< InputDataType, OutputDataType > , PoissonNLLLoss< InputDataType, OutputDataType > , ReconstructionLoss< InputDataType, OutputDataType, DistType > , SigmoidCrossEntropyError< InputDataType, OutputDataType > , SoftMarginLoss< InputDataType, OutputDataType > , RBM< InitializationRuleType, DataType, PolicyType > , DatasetMapper< PolicyType, InputType > , LRegularizer< TPower > , OrthogonalRegularizer , ImageInfo , RNN< OutputLayerType, InitializationRuleType, CustomLayers > , DrusillaSelect< MatType > , MaxAbsScaler , QDAFN< MatType > , BayesianLinearRegression , MeanNormalization , CFType< DecompositionPolicy, NormalizationType > , CFModel , MinMaxScaler , BatchSVDPolicy , BiasSVDPolicy , PCAWhitening , NMFPolicy , RandomizedSVDPolicy , StandardScaler , RegSVDPolicy , SVDCompletePolicy , ZCAWhitening , SVDIncompletePolicy , SVDPlusPlusPolicy , StringEncoding< EncodingPolicyType, DictionaryType > , CombinedNormalization< NormalizationTypes > , ItemMeanNormalization , StringEncodingDictionary< Token > , NoNormalization , OverallMeanNormalization , StringEncodingDictionary< boost::string_view > , UserMeanNormalization , ZScoreNormalization , StringEncodingDictionary< int > , DecisionStump< MatType > , DecisionTree< FitnessFunction, NumericSplitType, CategoricalSplitType, DimensionSelectionType, ElemType, NoRecursion > , BagOfWordsEncodingPolicy , DTree< MatType, TagType > , FastMKS< KernelType, MatType, TreeType > , DictionaryEncodingPolicy , FastMKSModel , FastMKSStat , TfIdfEncodingPolicy , DiagonalConstraint , DiagonalGMM , DiagonalGaussianDistribution , EigenvalueRatioConstraint , EMFit< InitialClusteringType, CovarianceConstraintPolicy, Distribution > , DiscreteDistribution , GMM , NoConstraint , GaussianDistribution , PositiveDefiniteConstraint , HMMModel , LaplaceDistribution , BinaryNumericSplit< FitnessFunction, ObservationType > , BinaryNumericSplitInfo< ObservationType > , RegressionDistribution , CategoricalSplitInfo , HoeffdingCategoricalSplit< FitnessFunction > , CauchyKernel , HoeffdingNumericSplit< FitnessFunction, ObservationType > , HoeffdingTree< FitnessFunction, NumericSplitType, CategoricalSplitType > , CosineDistance , HoeffdingTreeModel , NumericSplitInfo< ObservationType > , EpanechnikovKernel , KDE< KernelType, MetricType, MatType, TreeType, DualTreeTraversalType, SingleTreeTraversalType > , KDEModel , ExampleKernel , KDEStat , AllowEmptyClusters , GaussianKernel , KillEmptyClusters , KMeans< MetricType, InitialPartitionPolicy, EmptyClusterPolicy, LloydStepType, MatType > , HyperbolicTangentKernel , MaxVarianceNewCluster , RandomPartition , LaplacianKernel , RefinedStart , LARS , LinearKernel , LinearRegression , LinearSVM< MatType > , PolynomialKernel , SparseCoding , SoftmaxRegression , RASearch< SortPolicy, MetricType, MatType, TreeType > , LocalCoordinateCoding , RAModel< SortPolicy > , RSModel , LogisticRegression< MatType > , SphericalKernel , RandomForest< FitnessFunction, DimensionSelectionType, NumericSplitType, CategoricalSplitType, ElemType > , ScalingModel , Perceptron< LearnPolicy, WeightInitializationPolicy, MatType > , LSHSearch< SortPolicy, MatType > , NaiveBayesClassifier< ModelMatType > , TriangularKernel , NeighborSearch< SortPolicy, MetricType, MatType, TreeType, DualTreeTraversalType, SingleTreeTraversalType > , NeighborSearchStat< SortPolicy > , RangeType< T > , NSModel< SortPolicy > , BLEU< ElemType, PrecisionType > , IoU< UseCoordinates > , RangeSearch< MetricType, MatType, TreeType > , RangeSearchStat , IPMetric< KernelType > , LMetric< TPower, TTakeRoot > , RAQueryStat< SortPolicy > , MahalanobisDistance< TakeRoot > , NMS< UseCoordinates > , BallBound< MetricType, VecType > , BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType > , CoverTree< MetricType, StatisticType, MatType, RootPointPolicy > , HollowBallBound< TMetricType, ElemType > , HRectBound< MetricType, ElemType > , Octree< MetricType, StatisticType, MatType > , HilbertRTreeAuxiliaryInformation< TreeType, HilbertValueType > , NoAuxiliaryInformation< TreeType > , RPlusPlusTreeAuxiliaryInformation< TreeType > , RectangleTree< MetricType, StatisticType, MatType, SplitType, DescentType, AuxiliaryInformationType > , XTreeAuxiliaryInformation< TreeType >::SplitHistoryStruct , XTreeAuxiliaryInformation< TreeType > , HyperplaneBase< BoundT, ProjVectorT > , AxisParallelProjVector , ProjVector , SpillTree< MetricType, StatisticType, MatType, HyperplaneType, SplitType > , EmptyStatistic , AdaBoost< WeakLearnerType, MatType > , AdaBoostModel , AverageInitialization , GivenInitialization , RandomAcolInitialization< columnsToAverage > , RandomInitialization , NMFALSUpdate , NMFMultiplicativeDistanceUpdate , NMFMultiplicativeDivergenceUpdate , SVDBatchLearning , BRNN< OutputLayerType, MergeLayerType, MergeOutputType, InitializationRuleType, CustomLayers > , BernoulliDistribution< DataType > , NormalDistribution< DataType > , FFN< OutputLayerType, InitializationRuleType, CustomLayers > , GAN< Model, InitializationRuleType, Noise, PolicyType > , AdaptiveMaxPooling< InputDataType, OutputDataType > , AdaptiveMeanPooling< InputDataType, OutputDataType > , Add< InputDataType, OutputDataType > , AddMerge< InputDataType, OutputDataType, CustomLayers > , AlphaDropout< InputDataType, OutputDataType > , AtrousConvolution< ForwardConvolutionRule, BackwardConvolutionRule, GradientConvolutionRule, InputDataType, OutputDataType > , BaseLayer< ActivationFunction, InputDataType, OutputDataType > , BatchNorm< InputDataType, OutputDataType > , BilinearInterpolation< InputDataType, OutputDataType > , CReLU< InputDataType, OutputDataType > , CELU< InputDataType, OutputDataType > , Concat< InputDataType, OutputDataType, CustomLayers > , ConcatPerformance< OutputLayerType, InputDataType, OutputDataType > , Concatenate< InputDataType, OutputDataType > , Constant< InputDataType, OutputDataType > , Convolution< ForwardConvolutionRule, BackwardConvolutionRule, GradientConvolutionRule, InputDataType, OutputDataType > , DropConnect< InputDataType, OutputDataType > , Dropout< InputDataType, OutputDataType > , ELU< InputDataType, OutputDataType > , FastLSTM< InputDataType, OutputDataType > , FlexibleReLU< InputDataType, OutputDataType > , Glimpse< InputDataType, OutputDataType > , GRU< InputDataType, OutputDataType > , HardTanH< InputDataType, OutputDataType > , HardShrink< InputDataType, OutputDataType > , Highway< InputDataType, OutputDataType, CustomLayers > , Join< InputDataType, OutputDataType > , LayerNorm< InputDataType, OutputDataType > , LeakyReLU< InputDataType, OutputDataType > , Linear< InputDataType, OutputDataType, RegularizerType > , Linear3D< InputDataType, OutputDataType, RegularizerType > , LinearNoBias< InputDataType, OutputDataType, RegularizerType > , LogSoftMax< InputDataType, OutputDataType > , Lookup< InputDataType, OutputDataType > , LSTM< InputDataType, OutputDataType >
• Set() : SumTree< T >
• SetDimensionality() : DatasetMapper< PolicyType, InputType >
• SetInputHeightVisitor() : SetInputHeightVisitor
• SetInputWidthVisitor() : SetInputWidthVisitor
• SetPassed() : IO
• SetState() : Pendulum::State
• ShortDescription() : ShortDescription
• ShortDescriptionWrapper() : ShortDescriptionWrapper
• ShrinkBoundForBound() : RectangleTree< MetricType, StatisticType, MatType, SplitType, DescentType, AuxiliaryInformationType >
• ShrinkBoundForPoint() : RectangleTree< MetricType, StatisticType, MatType, SplitType, DescentType, AuxiliaryInformationType >
• Shuffle() : SoftmaxErrorFunction< MetricType > , RegularizedSVDFunction< MatType > , SoftmaxRegressionFunction , RBM< InitializationRuleType, DataType, PolicyType > , LMNNFunction< MetricType > , BiasSVDFunction< MatType > , KFoldCV< MLAlgorithm, Metric, MatType, PredictionsType, WeightsType > , BRNN< OutputLayerType, MergeLayerType, MergeOutputType, InitializationRuleType, CustomLayers > , FFN< OutputLayerType, InitializationRuleType, CustomLayers > , GAN< Model, InitializationRuleType, Noise, PolicyType > , RNN< OutputLayerType, InitializationRuleType, CustomLayers > , LinearSVMFunction< MatType > , LogisticRegressionFunction< MatType > , SVDPlusPlusFunction< MatType >
• Sigmoid() : SparseAutoencoder , SparseAutoencoderFunction
• SigmoidCrossEntropyError() : SigmoidCrossEntropyError< InputDataType, OutputDataType >
• Similarity() : CosineEmbeddingLoss< InputDataType, OutputDataType >
• SimilarityInterpolation() : SimilarityInterpolation
• SimpleCV() : SimpleCV< MLAlgorithm, Metric, MatType, PredictionsType, WeightsType >
• SimpleDQN() : SimpleDQN< OutputLayerType, InitType, NetworkType >
• SimpleResidueTermination() : SimpleResidueTermination
• SimpleToleranceTermination() : SimpleToleranceTermination< MatType >
• SingleMode() : RAModel< SortPolicy > , RASearch< SortPolicy, MetricType, MatType, TreeType > , FastMKSModel , RSModel , RangeSearch< MetricType, MatType, TreeType > , FastMKS< KernelType, MatType, TreeType > , FastMKSModel , RangeSearch< MetricType, MatType, TreeType > , RSModel , RAModel< SortPolicy >
• SingleSampleLimit() : RAModel< SortPolicy > , RASearch< SortPolicy, MetricType, MatType, TreeType >
• SingleTreeTraverser() : BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType >::SingleTreeTraverser< RuleType > , Octree< MetricType, StatisticType, MatType >::SingleTreeTraverser< RuleType > , RectangleTree< MetricType, StatisticType, MatType, SplitType, DescentType, AuxiliaryInformationType >::SingleTreeTraverser< RuleType > , CoverTree< MetricType, StatisticType, MatType, RootPointPolicy >::SingleTreeTraverser< RuleType >
• Size() : RandomReplay< EnvironmentType > , StringEncodingDictionary< Token > , SpatialDropout< InputDataType, OutputDataType > , StringEncodingDictionary< int > , StringEncodingDictionary< boost::string_view > , SpatialDropout< InputDataType, OutputDataType > , PrioritizedReplay< EnvironmentType >
• SizeAverage() : VRClassReward< InputDataType, OutputDataType >
• SlabMean() : RBM< InitializationRuleType, DataType, PolicyType >
• SlabPenalty() : RBM< InitializationRuleType, DataType, PolicyType >
• Smooth() : HMM< Distribution > , DiceLoss< InputDataType, OutputDataType > , HMMRegression
• SmoothIdf() : TfIdfEncodingPolicy
• SoftDelete() : RectangleTree< MetricType, StatisticType, MatType, SplitType, DescentType, AuxiliaryInformationType >
• SoftMarginLoss() : SoftMarginLoss< InputDataType, OutputDataType >
• Softmax() : Softmax< InputDataType, OutputDataType >
• SoftmaxErrorFunction() : SoftmaxErrorFunction< MetricType >
• SoftmaxRegression() : SoftmaxRegression
• SoftmaxRegressionFunction() : SoftmaxRegressionFunction
• Softmin() : Softmin< InputDataType, OutputDataType >
• SoftShrink() : SoftShrink< InputDataType, OutputDataType >
• SoftUpdate() : SAC< EnvironmentType, QNetworkType, PolicyNetworkType, UpdaterType, ReplayType >
• SortTask() : SortTask
• SparseAutoencoder() : SparseAutoencoder
• SparseAutoencoderFunction() : SparseAutoencoderFunction
• SparseCoding() : SparseCoding
• SpatialDropout() : SpatialDropout< InputDataType, OutputDataType >
• SphericalKernel() : SphericalKernel
• SpikeBias() : RBM< InitializationRuleType, DataType, PolicyType >
• SpikeMean() : RBM< InitializationRuleType, DataType, PolicyType >
• SpillDualTreeTraverser() : SpillTree< MetricType, StatisticType, MatType, HyperplaneType, SplitType >::SpillDualTreeTraverser< MetricType, StatisticType, MatType, HyperplaneType, SplitType >
• SpillSingleTreeTraverser() : SpillTree< MetricType, StatisticType, MatType, HyperplaneType, SplitType >::SpillSingleTreeTraverser< MetricType, StatisticType, MatType, HyperplaneType, SplitType >
• SpillTree() : SpillTree< MetricType, StatisticType, MatType, HyperplaneType, SplitType >
• Split() : DecisionStump< MatType > , HoeffdingNumericSplit< FitnessFunction, ObservationType > , BinaryNumericSplit< FitnessFunction, ObservationType > , DecisionStump< MatType > , HoeffdingCategoricalSplit< FitnessFunction >
• SplitAuxiliaryInfo() : RPlusPlusTreeAuxiliaryInformation< TreeType > , NoAuxiliaryInformation< TreeType >
• SplitByAnyOf() : SplitByAnyOf
• SplitCheck() : HoeffdingTree< FitnessFunction, NumericSplitType, CategoricalSplitType >
• SplitDim() : DTree< MatType, TagType >
• SplitDimension() : DecisionTree< FitnessFunction, NumericSplitType, CategoricalSplitType, DimensionSelectionType, ElemType, NoRecursion > , DecisionStump< MatType > , HoeffdingTree< FitnessFunction, NumericSplitType, CategoricalSplitType >
• SplitHistory() : XTreeAuxiliaryInformation< TreeType >
• SplitHistoryStruct() : XTreeAuxiliaryInformation< TreeType >::SplitHistoryStruct
• SplitIfBetter() : BestBinaryNumericSplit< FitnessFunction > , AllCategoricalSplit< FitnessFunction >
• SplitInfo() : VantagePointSplit< BoundType, MatType, MaxNumSamples >::SplitInfo , Octree< MetricType, StatisticType, MatType >::SplitType::SplitInfo , VantagePointSplit< BoundType, MatType, MaxNumSamples >::SplitInfo
• SplitLeafNode() : RPlusTreeSplit< SplitPolicyType, SweepType > , RStarTreeSplit , HilbertRTreeSplit< splitOrder > , RTreeSplit , XTreeSplit
• SplitNode() : MeanSplit< BoundType, MatType > , MidpointSplit< BoundType, MatType > , RPTreeMeanSplit< BoundType, MatType > , VantagePointSplit< BoundType, MatType, MaxNumSamples > , RPTreeMaxSplit< BoundType, MatType >
• SplitNonLeafNode() : RTreeSplit , RStarTreeSplit , XTreeSplit , HilbertRTreeSplit< splitOrder > , RPlusTreeSplit< SplitPolicyType, SweepType >
• SplitPointIndex() : CosineTree
• SplitSpace() : MeanSpaceSplit< MetricType, MatType > , MidpointSpaceSplit< MetricType, MatType >
• SplitValue() : DTree< MatType, TagType >
• SrcSeqLen() : MultiheadAttention< InputDataType, OutputDataType, RegularizerType >
• StandardDeviation() : NormalDistribution< DataType > , ReinforceNormal< InputDataType, OutputDataType >
• Start() : DTree< MatType, TagType > , Timer
• StartTimer() : Timers
• Stat() : SpillTree< MetricType, StatisticType, MatType, HyperplaneType, SplitType > , Octree< MetricType, StatisticType, MatType > , ExampleTree< MetricType, StatisticType, MatType > , CoverTree< MetricType, StatisticType, MatType, RootPointPolicy > , Octree< MetricType, StatisticType, MatType > , SpillTree< MetricType, StatisticType, MatType, HyperplaneType, SplitType > , ExampleTree< MetricType, StatisticType, MatType > , RectangleTree< MetricType, StatisticType, MatType, SplitType, DescentType, AuxiliaryInformationType > , BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType > , RectangleTree< MetricType, StatisticType, MatType, SplitType, DescentType, AuxiliaryInformationType > , CoverTree< MetricType, StatisticType, MatType, RootPointPolicy >
• State() : ContinuousDoublePoleCart::State , MountainCar::State , Pendulum::State , ContinuousActionEnv::State , CartPole::State , ContinuousMountainCar::State , QLearning< EnvironmentType, NetworkType, UpdaterType, PolicyType, ReplayType > , DiscreteActionEnv::State , CartPole::State , SAC< EnvironmentType, QNetworkType, PolicyNetworkType, UpdaterType, ReplayType > , DiscreteActionEnv::State , Pendulum::State , MountainCar::State , DoublePoleCart::State , QLearning< EnvironmentType, NetworkType, UpdaterType, PolicyType, ReplayType > , ContinuousActionEnv::State , ContinuousDoublePoleCart::State , Acrobot::State , ContinuousMountainCar::State
• StaticLowerBoundMovement() : DualTreeKMeansStatistic
• StaticPruned() : DualTreeKMeansStatistic
• StaticUpperBoundMovement() : DualTreeKMeansStatistic
• Stddev() : ZScoreNormalization
• Step() : OneStepSarsaWorker< EnvironmentType, NetworkType, UpdaterType, PolicyType > , OneStepQLearningWorker< EnvironmentType, NetworkType, UpdaterType, PolicyType > , NStepQLearningWorker< EnvironmentType, NetworkType, UpdaterType, PolicyType >
• StepLimit() : TrainingConfig
• StepSize() : TrainingConfig
• StepsPerformed() : Pendulum , ContinuousDoublePoleCart , MountainCar , Acrobot , DoublePoleCart , CartPole , ContinuousMountainCar
• Stochastic() : Reparametrization< InputDataType, OutputDataType >
• Stop() : Timer
• StopAllTimers() : Timers
• StopTimer() : Timers
• Store() : PrioritizedReplay< EnvironmentType > , RandomReplay< EnvironmentType >
• StoreSettings() : IO
• Strategy() : Imputer< T, MapperType, StrategyType >
• StrideHeight() : AtrousConvolution< ForwardConvolutionRule, BackwardConvolutionRule, GradientConvolutionRule, InputDataType, OutputDataType > , MeanPooling< InputDataType, OutputDataType > , MaxPooling< InputDataType, OutputDataType > , Convolution< ForwardConvolutionRule, BackwardConvolutionRule, GradientConvolutionRule, InputDataType, OutputDataType > , TransposedConvolution< ForwardConvolutionRule, BackwardConvolutionRule, GradientConvolutionRule, InputDataType, OutputDataType > , MaxPooling< InputDataType, OutputDataType > , MeanPooling< InputDataType, OutputDataType > , Convolution< ForwardConvolutionRule, BackwardConvolutionRule, GradientConvolutionRule, InputDataType, OutputDataType > , AtrousConvolution< ForwardConvolutionRule, BackwardConvolutionRule, GradientConvolutionRule, InputDataType, OutputDataType > , TransposedConvolution< ForwardConvolutionRule, BackwardConvolutionRule, GradientConvolutionRule, InputDataType, OutputDataType >
• StrideWidth() : MaxPooling< InputDataType, OutputDataType > , TransposedConvolution< ForwardConvolutionRule, BackwardConvolutionRule, GradientConvolutionRule, InputDataType, OutputDataType > , AtrousConvolution< ForwardConvolutionRule, BackwardConvolutionRule, GradientConvolutionRule, InputDataType, OutputDataType > , MeanPooling< InputDataType, OutputDataType > , TransposedConvolution< ForwardConvolutionRule, BackwardConvolutionRule, GradientConvolutionRule, InputDataType, OutputDataType > , Convolution< ForwardConvolutionRule, BackwardConvolutionRule, GradientConvolutionRule, InputDataType, OutputDataType > , MaxPooling< InputDataType, OutputDataType > , AtrousConvolution< ForwardConvolutionRule, BackwardConvolutionRule, GradientConvolutionRule, InputDataType, OutputDataType > , MeanPooling< InputDataType, OutputDataType >
• StringEncoding() : StringEncoding< EncodingPolicyType, DictionaryType >
• StringEncodingDictionary() : StringEncodingDictionary< boost::string_view > , StringEncodingDictionary< int >
• SubtreeLeaves() : DTree< MatType, TagType >
• SubtreeLeavesLogNegError() : DTree< MatType, TagType >
• Subview() : Subview< InputDataType, OutputDataType >
• SuccessProbability() : RAUtil , HoeffdingTree< FitnessFunction, NumericSplitType, CategoricalSplitType >
• Sum() : SumTree< T >
• SumHelper() : SumTree< T >
• SumTree() : SumTree< T >
• SVDBatchLearning() : SVDBatchLearning
• SVDCompleteIncrementalLearning() : SVDCompleteIncrementalLearning< arma::sp_mat > , SVDCompleteIncrementalLearning< MatType >
• SVDIncompleteIncrementalLearning() : SVDIncompleteIncrementalLearning
• SVDPlusPlus() : SVDPlusPlus< OptimizerType >
• SVDPlusPlusFunction() : SVDPlusPlusFunction< MatType >
• SVDPlusPlusPolicy() : SVDPlusPlusPolicy
• SVDWrapper() : SVDWrapper< Factorizer >
• SweepLeafNode() : MinimalCoverageSweep< SplitPolicy > , MinimalSplitsNumberSweep< SplitPolicy >
• SweepNonLeafNode() : MinimalCoverageSweep< SplitPolicy > , MinimalSplitsNumberSweep< SplitPolicy >
• Sweeps() : Radical