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Dimensionality reduction algorithms Dimensionality reduction techniques
This module provides algorithms for reducing the dimensionality of data, which is useful for visualization, feature extraction, and reducing computational complexity.
Structs§
- LDA
- Linear Discriminant Analysis (LDA) for dimensionality reduction
- PCA
- Principal Component Analysis (PCA) dimensionality reduction
- TSNE
- t-SNE (t-distributed Stochastic Neighbor Embedding) for dimensionality reduction
- TruncatedSVD
- Truncated Singular Value Decomposition (SVD) for dimensionality reduction
Functions§
- trustworthiness
- Calculate trustworthiness score for a dimensionality reduction