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Information-Theoretic Kernel Methods
This module implements kernel approximation methods based on information theory, including mutual information kernels, entropy-based feature selection, and KL-divergence kernel features.
Structs§
- Entropy
Feature Selector - Entropy-based Feature Selection
- Fitted
Entropy Feature Selector - Fitted Entropy Feature Selector FittedEntropyFeatureSelector
- Fitted
Information Bottleneck Extractor - Fitted Information Bottleneck Extractor FittedInformationBottleneckExtractor
- FittedKL
Divergence Kernel - Fitted KL-Divergence Kernel FittedKLDivergenceKernel
- Fitted
Mutual Information Kernel - Fitted Mutual Information Kernel FittedMutualInformationKernel
- Information
Bottleneck Extractor - Information Bottleneck Feature Extractor
- KLDivergence
Kernel - KL-Divergence Kernel Features
- Mutual
Information Kernel - Mutual Information Kernel Approximation
Enums§
- Entropy
Selection Method - Methods for entropy-based feature selection EntropySelectionMethod
- KLReference
Distribution - Reference distributions for KL-divergence computation KLReferenceDistribution