Here is a list of all class members with links to the classes they belong to:
- m -
- MahalanobisDistance() : MahalanobisDistance< TakeRoot >
- MajorityClass() : BinaryNumericSplit< FitnessFunction, ObservationType >, HoeffdingCategoricalSplit< FitnessFunction >, HoeffdingNumericSplit< FitnessFunction, ObservationType >, HoeffdingTree< FitnessFunction, NumericSplitType, CategoricalSplitType >
- MajorityProbability() : BinaryNumericSplit< FitnessFunction, ObservationType >, HoeffdingCategoricalSplit< FitnessFunction >, HoeffdingNumericSplit< FitnessFunction, ObservationType >, HoeffdingTree< FitnessFunction, NumericSplitType, CategoricalSplitType >
- MakeInPlaceCopy() : IO
- map : BindingInfo
- MapFirstPass() : DatasetMapper< PolicyType, InputType >, IncrementPolicy, MissingPolicy
- MappedType : IncrementPolicy, MissingPolicy
- Mapper() : Imputer< T, MapperType, StrategyType >
- Mapping() : StringEncodingDictionary< Token >, StringEncodingDictionary< boost::string_view >, StringEncodingDictionary< int >
- Mappings() : AdaBoostModel
- MapString() : DatasetMapper< PolicyType, InputType >, IncrementPolicy, MissingPolicy
- MapType : StringEncodingDictionary< Token >, StringEncodingDictionary< boost::string_view >, StringEncodingDictionary< int >
- Margin() : CosineEmbeddingLoss< InputDataType, OutputDataType >, MarginRankingLoss< InputDataType, OutputDataType >
- MarginRankingLoss() : MarginRankingLoss< InputDataType, OutputDataType >
- Mask() : AlphaDropout< InputDataType, OutputDataType >, SplitByAnyOf
- MaskType : SplitByAnyOf
- Mat : BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType >, CoverTree< MetricType, StatisticType, MatType, RootPointPolicy >, Octree< MetricType, StatisticType, MatType >, RectangleTree< MetricType, StatisticType, MatType, SplitType, DescentType, AuxiliaryInformationType >, SpillTree< MetricType, StatisticType, MatType, HyperplaneType, SplitType >
- MatrixCompletion() : MatrixCompletion
- MatUtriCholFactor() : LARS
- MAX_ABS_SCALER : ScalingModel
- MAX_RP_TREE : NSModel< SortPolicy >, RSModel
- MaxDistance() : BallBound< MetricType, VecType >, HollowBallBound< TMetricType, ElemType >, HRectBound< MetricType, ElemType >, BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType >, CoverTree< MetricType, StatisticType, MatType, RootPointPolicy >, ExampleTree< MetricType, StatisticType, MatType >, Octree< MetricType, StatisticType, MatType >, RectangleTree< MetricType, StatisticType, MatType, SplitType, DescentType, AuxiliaryInformationType >, SpillTree< MetricType, StatisticType, MatType, HyperplaneType, SplitType >
- MaxIterations() : CompleteIncrementalTermination< TerminationPolicy >, IncompleteIncrementalTermination< TerminationPolicy >, MaxIterationTermination, SimpleResidueTermination
- maxIterations : SimpleResidueTermination
- MaxIterations() : SimpleToleranceTermination< MatType >, ValidationRMSETermination< MatType >, BiasSVDPolicy, RandomizedSVDPolicy, RegSVDPolicy, SVDPlusPlusPolicy, EMFit< InitialClusteringType, CovarianceConstraintPolicy, Distribution >, KMeans< MetricType, InitialPartitionPolicy, EmptyClusterPolicy, LloydStepType, MatType >, LocalCoordinateCoding, MeanShift< UseKernel, KernelType, MatType >, RandomizedBlockKrylovSVDPolicy, RandomizedSVDPolicy, Perceptron< LearnPolicy, WeightInitializationPolicy, MatType >, SparseCoding, RandomizedBlockKrylovSVD, RandomizedSVD
- MaxIterationTermination() : MaxIterationTermination
- MaxLeafSize() : RectangleTree< MetricType, StatisticType, MatType, SplitType, DescentType, AuxiliaryInformationType >
- MaxNeighborDistance() : DTBStat
- MaxNumChildren() : RectangleTree< MetricType, StatisticType, MatType, SplitType, DescentType, AuxiliaryInformationType >
- MaxOrder() : BLEU< ElemType, PrecisionType >
- MaxPooling() : MaxPooling< InputDataType, OutputDataType >
- MaxRange() : ColumnsToBlocks
- MaxReward() : RewardClipping< EnvironmentType >
- MaxSamples() : HoeffdingTree< FitnessFunction, NumericSplitType, CategoricalSplitType >
- MaxSteps() : Acrobot, CartPole, ContinuousDoublePoleCart, ContinuousMountainCar, DoublePoleCart, MountainCar, Pendulum
- MaxVals() : DTree< MatType, TagType >
- MaxValue() : HardTanH< InputDataType, OutputDataType >
- MaxVarianceNewCluster() : MaxVarianceNewCluster
- MCAlpha() : KDEStat
- MCBeta() : KDEStat
- MCBreakCoef() : KDE< KernelType, MetricType, MatType, TreeType, DualTreeTraversalType, SingleTreeTraversalType >
- mcBreakCoef : KDEDefaultParams
- MCBreakCoefficient() : KDEModel
- MCBreakCoefVisitor() : MCBreakCoefVisitor
- MCEntryCoef() : KDE< KernelType, MetricType, MatType, TreeType, DualTreeTraversalType, SingleTreeTraversalType >
- mcEntryCoef : KDEDefaultParams
- MCEntryCoefficient() : KDEModel
- MCEntryCoefVisitor() : MCEntryCoefVisitor
- MCInitialSampleSize() : KDE< KernelType, MetricType, MatType, TreeType, DualTreeTraversalType, SingleTreeTraversalType >, KDEModel
- MCProb() : KDE< KernelType, MetricType, MatType, TreeType, DualTreeTraversalType, SingleTreeTraversalType >
- mcProb : KDEDefaultParams
- MCProbability() : KDEModel
- MCProbabilityVisitor() : MCProbabilityVisitor
- MCSampleSizeVisitor() : MCSampleSizeVisitor
- MDOption() : MDOption< T >
- Mean() : HuberLoss< InputDataType, OutputDataType >, L1Loss< InputDataType, OutputDataType >, LayerNorm< InputDataType, OutputDataType >, NormalDistribution< DataType >, PoissonNLLLoss< InputDataType, OutputDataType >, ItemMeanNormalization, OverallMeanNormalization, UserMeanNormalization, ZScoreNormalization, DiagonalGaussianDistribution, GaussianDistribution, LaplaceDistribution
- mean : RPTreeMeanSplit< BoundType, MatType >::SplitInfo
- MEAN_NORMALIZATION : ScalingModel
- MeanAbsolutePercentageError() : MeanAbsolutePercentageError< InputDataType, OutputDataType >
- MeanBiasError() : MeanBiasError< InputDataType, OutputDataType >
- MeanDistanceFromCluster() : SilhouetteScore
- MeanPooling() : MeanPooling< InputDataType, OutputDataType >
- Means() : NaiveBayesClassifier< ModelMatType >
- MeanShift() : MeanShift< UseKernel, KernelType, MatType >
- meanSplit : RPTreeMeanSplit< BoundType, MatType >::SplitInfo
- MeanSquaredError() : MeanSquaredError< InputDataType, OutputDataType >
- MeanSquaredLogarithmicError() : MeanSquaredLogarithmicError< InputDataType, OutputDataType >
- MergeInitialization() : MergeInitialization< WInitializationRuleType, HInitializationRuleType >
- Metric() : BallBound< MetricType, VecType >, HollowBallBound< TMetricType, ElemType >, HRectBound< MetricType, ElemType >, FastMKS< KernelType, MatType, TreeType >, KDE< KernelType, MetricType, MatType, TreeType, DualTreeTraversalType, SingleTreeTraversalType >, KMeans< MetricType, InitialPartitionPolicy, EmptyClusterPolicy, LloydStepType, MatType >
- metric : NeighborSearchRules< SortPolicy, MetricType, TreeType >
- Metric() : BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType >, CoverTree< MetricType, StatisticType, MatType, RootPointPolicy >, ExampleTree< MetricType, StatisticType, MatType >, Octree< MetricType, StatisticType, MatType >, RectangleTree< MetricType, StatisticType, MatType, SplitType, DescentType, AuxiliaryInformationType >, SpillTree< MetricType, StatisticType, MatType, HyperplaneType, SplitType >
- metric : VantagePointSplit< BoundType, MatType, MaxNumSamples >::SplitInfo
- MetricType : HollowBallBound< TMetricType, ElemType >, VantagePointSplit< BoundType, MatType, MaxNumSamples >
- Mid() : RangeType< T >
- MIE : CVBase< MLAlgorithm, MatType, PredictionsType, WeightsType >
- MIN_MAX_SCALER : ScalingModel
- MinDelta() : HyperParameterTuner< MLAlgorithm, Metric, CV, OptimizerType, MatType, PredictionsType, WeightsType >
- MinDistance() : BallBound< MetricType, VecType >, HollowBallBound< TMetricType, ElemType >, HRectBound< MetricType, ElemType >, BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType >, CoverTree< MetricType, StatisticType, MatType, RootPointPolicy >, ExampleTree< MetricType, StatisticType, MatType >, Octree< MetricType, StatisticType, MatType >, RectangleTree< MetricType, StatisticType, MatType, SplitType, DescentType, AuxiliaryInformationType >, SpillTree< MetricType, StatisticType, MatType, HyperplaneType, SplitType >
- MiniBatchDiscrimination() : MiniBatchDiscrimination< InputDataType, OutputDataType >
- MinimumBaseCases() : FastMKSRules< KernelType, TreeType >, KDERules< MetricType, KernelType, TreeType >, DualTreeKMeansRules< MetricType, TreeType >, NeighborSearchRules< SortPolicy, MetricType, TreeType >, RASearchRules< SortPolicy, MetricType, TreeType >, RangeSearchRules< MetricType, TreeType >
- MinimumBoundDistance() : BinarySpaceTree< MetricType, StatisticType, MatType, BoundType, SplitType >, CoverTree< MetricType, StatisticType, MatType, RootPointPolicy >, Octree< MetricType, StatisticType, MatType >, RectangleTree< MetricType, StatisticType, MatType, SplitType, DescentType, AuxiliaryInformationType >, SpillTree< MetricType, StatisticType, MatType, HyperplaneType, SplitType >
- MinimumSamplesReqd() : RAUtil
- MinLeafSize() : RectangleTree< MetricType, StatisticType, MatType, SplitType, DescentType, AuxiliaryInformationType >
- MinMaxScaler() : MinMaxScaler
- MinNeighborDistance() : DTBStat
- MinNumberOfAdditionalArgs : TrainFormBase4< PT, WT, T1, T2 >, TrainFormBase5< PT, WT, T1, T2, T3 >, TrainFormBase6< PT, WT, T1, T2, T3, T4 >, TrainFormBase7< PT, WT, T1, T2, T3, T4, T5 >
- MinNumChildren() : RectangleTree< MetricType, StatisticType, MatType, SplitType, DescentType, AuxiliaryInformationType >
- MinRange() : ColumnsToBlocks
- MinResidue() : SimpleResidueTermination
- minResidue : SimpleResidueTermination
- MinResidue() : SimpleResidueTermination
- MinReward() : RewardClipping< EnvironmentType >
- MinSamples() : HoeffdingTree< FitnessFunction, NumericSplitType, CategoricalSplitType >
- MinVals() : DTree< MatType, TagType >
- MinValue() : HardTanH< InputDataType, OutputDataType >
- MinWidth() : BallBound< MetricType, VecType >, HollowBallBound< TMetricType, ElemType >, HRectBound< MetricType, ElemType >
- MissingPolicy() : MissingPolicy
- Mode() : KDE< KernelType, MetricType, MatType, TreeType, DualTreeTraversalType, SingleTreeTraversalType >
- mode : KDEDefaultParams
- Mode() : KDEModel
- Model() : AddMerge< InputDataType, OutputDataType, CustomLayers >, Concat< InputDataType, OutputDataType, CustomLayers >, DropConnect< InputDataType, OutputDataType >, FFN< OutputLayerType, InitializationRuleType, CustomLayers >, GRU< InputDataType, OutputDataType >, Highway< InputDataType, OutputDataType, CustomLayers >, MultiplyMerge< InputDataType, OutputDataType, CustomLayers >, Recurrent< InputDataType, OutputDataType, CustomLayers >, RecurrentAttention< InputDataType, OutputDataType >, Sequential< InputDataType, OutputDataType, Residual, CustomLayers >, VRClassReward< InputDataType, OutputDataType >, KFoldCV< MLAlgorithm, Metric, MatType, PredictionsType, WeightsType >, SimpleCV< MLAlgorithm, Metric, MatType, PredictionsType, WeightsType >
- ModifiedGramSchmidt() : CosineTree
- Momentum() : BatchNorm< InputDataType, OutputDataType >
- MonoSearchVisitor() : MonoSearchVisitor
- MonteCarlo() : KDE< KernelType, MetricType, MatType, TreeType, DualTreeTraversalType, SingleTreeTraversalType >
- monteCarlo : KDEDefaultParams
- MonteCarlo() : KDEModel
- MonteCarloError() : CosineTree
- MonteCarloVisitor() : MonteCarloVisitor
- MountainCar() : MountainCar
- mu : VantagePointSplit< BoundType, MatType, MaxNumSamples >::SplitInfo
- MultiheadAttention() : MultiheadAttention< InputDataType, OutputDataType, RegularizerType >
- MultipleRandomDimensionSelect() : MultipleRandomDimensionSelect
- MultiplyConstant() : MultiplyConstant< InputDataType, OutputDataType >
- MultiplyMerge() : MultiplyMerge< InputDataType, OutputDataType, CustomLayers >
- MVU() : MVU