This technique takes advantage of the kernel trick that can be used in PCA. This is a tutorial only and is slow for large data sets.
In line 30 the kernel can be changed. Any Kernel should do it.
Ref : http://www.eecs.berkeley.edu/~wainwrig/stat241b/scholkopf_kernel.pdf
인용 양식
Ambarish Jash (2026). Kernel PCA (https://kr.mathworks.com/matlabcentral/fileexchange/27319-kernel-pca), MATLAB Central File Exchange. 검색 날짜: .
MATLAB 릴리스 호환 정보
개발 환경:
R2009b
모든 릴리스와 호환
플랫폼 호환성
Windows macOS Linux카테고리
- AI and Statistics > Statistics and Machine Learning Toolbox > Dimensionality Reduction and Feature Extraction >
- AI and Statistics > Statistics and Machine Learning Toolbox > Regression > Nonlinear Regression >
Help Center 및 MATLAB Answers에서 Dimensionality Reduction and Feature Extraction에 대해 자세히 알아보기
태그
| 버전 | 게시됨 | 릴리스 정보 | |
|---|---|---|---|
| 1.0.0.0 |
