Clustering and latent structure · MLD-0601
Kernel PCA
Principal component analysis performed implicitly in a kernel feature space.
Original reference page · detailed expansion pending. Original definitions, examples, notes and citations are preserved below. New examples are illustrative, not benchmark results.
Original example
Extract nonlinear components.
Original caveat
Out-of-sample transforms and large kernel matrices require care.
Context and aliases
Level: Intermediate. Stages: Training · Data · Evaluation.
Tags: ML · DL.
Aliases: None recorded.
Related concepts
Original references
- scikit-learn: clustering ↗ · Reference link
- scikit-learn: matrix decomposition ↗ · Reference link
- scikit-learn: manifold learning ↗ · Reference link
- scikit-learn: novelty and outlier detection ↗ · Reference link
- Original reference URL ↗