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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
Cite As
Ambarish Jash (2026). Kernel PCA (https://in.mathworks.com/matlabcentral/fileexchange/27319-kernel-pca), MATLAB Central File Exchange. Retrieved .
Categories
Find more on Dimensionality Reduction and Feature Extraction in Help Center and MATLAB Answers
General Information
- Version 1.0.0.0 (2.17 KB)
MATLAB Release Compatibility
- Compatible with any release
Platform Compatibility
- Windows
- macOS
- Linux
| Version | Published | Release Notes | Action |
|---|---|---|---|
| 1.0.0.0 |
