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Kernel PCA

version (164 KB) by Bhartendu
Kernel PCA analysis with Kernel ridge regression & SVM regression


Updated 26 May 2017

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Refer to 6.2.1 KPCA, Kernel Methods for Pattern Analysis, John Shawe-Taylor University of Southampton, Nello Cristianini University of California at Davis
Refer to 6.2.2 Kernel Ridge Regression, An Introduction to Support Vector Machines and Other Kernel-based Learning Methods, Nello Cristianini and John Shawe-Taylor

Kernel PCA:
Kernel PCA is the application of PCA in a kernel-defined feature space making use of the dual representation.

Reference: (for SVR) Reference: (for Ridge regression)

Cite As

Bhartendu (2021). Kernel PCA (, MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2016a
Compatible with any release
Platform Compatibility
Windows macOS Linux

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