Here is a list of all class members with links to the classes they belong to:

- e -

• EarthMoverDistance() : EarthMoverDistance< InputDataType, OutputDataType >
• EdgePair() : EdgePair
• EffectiveError() : NeighborSearch< SortPolicy, MetricType, MatType, TreeType, DualTreeTraversalType, SingleTreeTraversalType >
• EigenvalueRatioConstraint() : EigenvalueRatioConstraint
• EigenValues() : PCAWhitening , ZCAWhitening
• EigenVectors() : ZCAWhitening , PCAWhitening
• ElemType : HilbertRTreeAuxiliaryInformation< TreeType, HilbertValueType > , RPlusPlusTreeAuxiliaryInformation< TreeType > , BallBound< MetricType, VecType > , RectangleTree< MetricType, StatisticType, MatType, SplitType, DescentType, AuxiliaryInformationType > , SpillTree< MetricType, StatisticType, MatType, HyperplaneType, SplitType > , BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType > , FastLSTM< InputDataType, OutputDataType > , RBM< InitializationRuleType, DataType, PolicyType > , RPTreeMaxSplit< BoundType, MatType > , DTree< MatType, TagType > , NaiveBayesClassifier< ModelMatType > , RPTreeMeanSplit< BoundType, MatType > , VantagePointSplit< BoundType, MatType, MaxNumSamples > , CoverTree< MetricType, StatisticType, MatType, RootPointPolicy > , Octree< MetricType, StatisticType, MatType >
• ElkanKMeans() : ElkanKMeans< MetricType, MatType >
• ELU() : ELU< InputDataType, OutputDataType >
• EmbedDim() : MultiheadAttention< InputDataType, OutputDataType, RegularizerType >
• EmbeddingSize() : Lookup< InputDataType, OutputDataType >
• EMFit() : EMFit< InitialClusteringType, CovarianceConstraintPolicy, Distribution >
• Emission() : HMM< Distribution >
• emission : HMM< Distribution >
• Emission() : HMM< Distribution >
• EmptyCluster() : AllowEmptyClusters , KillEmptyClusters , MaxVarianceNewCluster
• EmptyClusterAction() : KMeans< MetricType, InitialPartitionPolicy, EmptyClusterPolicy, LloydStepType, MatType >
• EmptyLoss() : EmptyLoss< InputDataType, OutputDataType >
• EmptyStatistic() : EmptyStatistic
• Enabled() : Timers
• EnableTiming() : Timer
• Encode() : StringEncoding< EncodingPolicyType, DictionaryType > , BagOfWordsEncodingPolicy , DictionaryEncodingPolicy , TfIdfEncodingPolicy , LocalCoordinateCoding , Acrobot::State , CartPole::State , ContinuousDoublePoleCart::State , ContinuousMountainCar::State , DoublePoleCart::State , DiscreteActionEnv::State , ContinuousActionEnv::State , MountainCar::State , Pendulum::State , SparseCoding
• Encoding() : PositionalEncoding< InputDataType, OutputDataType >
• EncodingPolicy() : StringEncoding< EncodingPolicyType, DictionaryType >
• End() : AllDimensionSelect , MultipleRandomDimensionSelect , RandomDimensionSelect , DTree< MatType, TagType >
• EndCol() : Subview< InputDataType, OutputDataType >
• EndRow() : Subview< InputDataType, OutputDataType >
• Enter() : PathCacher
• Environment() : AsyncLearning< WorkerType, EnvironmentType, NetworkType, UpdaterType, PolicyType > , RewardClipping< EnvironmentType > , QLearning< EnvironmentType, NetworkType, UpdaterType, PolicyType, ReplayType >
• EPANECHNIKOV_KERNEL : FastMKSModel , KDEModel
• EpanechnikovKernel() : EpanechnikovKernel
• Episode() : QLearning< EnvironmentType, NetworkType, UpdaterType, PolicyType, ReplayType > , SAC< EnvironmentType, QNetworkType, PolicyNetworkType, UpdaterType, ReplayType >
• Eps() : CrossEntropyError< InputDataType, OutputDataType > , PoissonNLLLoss< InputDataType, OutputDataType >
• epsilon : NeighborSearchRules< SortPolicy, MetricType, TreeType >
• Epsilon() : PCAWhitening , ZCAWhitening , BatchNorm< InputDataType, OutputDataType > , LayerNorm< InputDataType, OutputDataType > , VirtualBatchNorm< InputDataType, OutputDataType > , NeighborSearch< SortPolicy, MetricType, MatType, TreeType, DualTreeTraversalType, SingleTreeTraversalType > , NSModel< SortPolicy > , QUICSVDPolicy , RandomizedSVD , GreedyPolicy< EnvironmentType >
• Err() : RegressionDistribution
• Estimate() : HMM< Distribution > , LaplaceDistribution , EMFit< InitialClusteringType, CovarianceConstraintPolicy, Distribution > , HMM< Distribution > , HMMRegression
• EstimateRadius() : MeanShift< UseKernel, KernelType, MatType >
• Evaluate() : Recall< AS, PositiveClass > , SphericalKernel , FFN< OutputLayerType, InitializationRuleType, CustomLayers > , SoftmaxRegressionFunction , EpanechnikovKernel , ExampleKernel , EpanechnikovKernel , LinearSVMFunction< MatType > , KDEModel , GaussianKernel , KDE< KernelType, MetricType, MatType, TreeType, DualTreeTraversalType, SingleTreeTraversalType > , HyperbolicTangentKernel , LogisticRegressionFunction< MatType > , LinearKernel , LogisticRegressionFunction< MatType > , LMNNFunction< MetricType > , BRNN< OutputLayerType, MergeLayerType, MergeOutputType, InitializationRuleType, CustomLayers > , KDE< KernelType, MetricType, MatType, TreeType, DualTreeTraversalType, SingleTreeTraversalType > , BiasSVDFunction< MatType > , PolynomialKernel , PSpectrumStringKernel , IoU< UseCoordinates > , RegularizedSVDFunction< MatType > , SoftmaxErrorFunction< MetricType > , SparseAutoencoderFunction , NMS< UseCoordinates > , BRNN< OutputLayerType, MergeLayerType, MergeOutputType, InitializationRuleType, CustomLayers > , FFN< OutputLayerType, InitializationRuleType, CustomLayers > , TriangularKernel , FFN< OutputLayerType, InitializationRuleType, CustomLayers > , IPMetric< KernelType > , LMetric< TPower, TTakeRoot > , RegularizedSVDFunction< MatType > , MahalanobisDistance< TakeRoot > , TriangularKernel , FFN< OutputLayerType, InitializationRuleType, CustomLayers > , BLEU< ElemType, PrecisionType > , LRegularizer< TPower > , CVFunction< CVType, MLAlgorithm, TotalArgs, BoundArgs > , SVDPlusPlusFunction< MatType > , Precision< AS, PositiveClass > , F1< AS, PositiveClass > , SimpleCV< MLAlgorithm, Metric, MatType, PredictionsType, WeightsType > , OrthogonalRegularizer , RNN< OutputLayerType, InitializationRuleType, CustomLayers > , InformationGain , RNN< OutputLayerType, InitializationRuleType, CustomLayers > , SphericalKernel , LaplacianKernel , MSE , HoeffdingInformationGain , LaplacianKernel , KDEModel , CosineDistance , SoftmaxRegressionFunction , LMNNFunction< MetricType > , LinearSVMFunction< MatType > , SoftmaxErrorFunction< MetricType > , CauchyKernel , R2Score , GAN< Model, InitializationRuleType, Noise, PolicyType > , BiasSVDFunction< MatType > , KDE< KernelType, MetricType, MatType, TreeType, DualTreeTraversalType, SingleTreeTraversalType > , GiniImpurity , GAN< Model, InitializationRuleType, Noise, PolicyType > , GiniGain , SVDPlusPlusFunction< MatType > , KFoldCV< MLAlgorithm, Metric, MatType, PredictionsType, WeightsType > , Accuracy , GAN< Model, InitializationRuleType, Noise, PolicyType > , NoRegularizer , RBM< InitializationRuleType, DataType, PolicyType >
• EvaluateFitnessFunction() : BinaryNumericSplit< FitnessFunction, ObservationType > , HoeffdingCategoricalSplit< FitnessFunction > , HoeffdingNumericSplit< FitnessFunction, ObservationType >
• EvaluatePtr() : InformationGain , GiniGain
• EvaluateWithGradient() : BRNN< OutputLayerType, MergeLayerType, MergeOutputType, InitializationRuleType, CustomLayers > , GAN< Model, InitializationRuleType, Noise, PolicyType > , FFN< OutputLayerType, InitializationRuleType, CustomLayers > , GAN< Model, InitializationRuleType, Noise, PolicyType > , RNN< OutputLayerType, InitializationRuleType, CustomLayers > , LMNNFunction< MetricType > , GAN< Model, InitializationRuleType, Noise, PolicyType > , LinearSVMFunction< MatType > , LMNNFunction< MetricType > , LinearSVMFunction< MatType > , LogisticRegressionFunction< MatType >
• ExactClone() : RectangleTree< MetricType, StatisticType, MatType, SplitType, DescentType, AuxiliaryInformationType >
• Example() : Example
• example : BindingDetails
• ExampleKernel() : ExampleKernel
• ExampleTree() : ExampleTree< MetricType, StatisticType, MatType >
• ExampleWrapper() : ExampleWrapper
• ExplorationSteps() : TrainingConfig
• ExtractSVD() : QUIC_SVD