Kernel PCA and Pre-Image Reconstruction

Version 3.2 (6.94 MB) by Quan Wang
standard PCA, Gaussian kernel PCA, polynomial kernel PCA, pre-image reconstruction
17.9K Downloads
Updated 15 Jun 2023

Kernel PCA and Pre-Image Reconstruction View Kernel PCA and Pre-Image Reconstruction on File Exchange arxiv

Overview

In this package, we implement standard PCA, kernel PCA, and pre-image reconstruction of Gaussian kernel PCA.

We also provide three demos:

  1. Two concentric spheres embedding;
  2. Face classification with PCA/kPCA;
  3. Active shape models with kPCA.

Standard PCA is not optimized for very high dimensional data. But our kernel PCA implementation is very efficient, and has been used in many research projects.

This library is also available at MathWorks:

pic

Citations

If you use this library, please cite:

@article{wang2012kernel,
  title={Kernel principal component analysis and its applications in face recognition and active shape models},
  author={Wang, Quan},
  journal={arXiv preprint arXiv:1207.3538},
  year={2012}
}

Cite As

Quan Wang (2024). Kernel PCA and Pre-Image Reconstruction (https://github.com/wq2012/kPCA/releases/tag/v3.2), GitHub. Retrieved .

MATLAB Release Compatibility
Created with R2012b
Compatible with any release
Platform Compatibility
Windows macOS Linux

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Version Published Release Notes
3.2

See release notes for this release on GitHub: https://github.com/wq2012/kPCA/releases/tag/v3.2

1.4.0.0

Fixed a fatal bug in pre-image reconstruction.

1.3.0.0

addpath('../code') in demo2

1.2.0.0

We replaces all demos, and the data used for the demo. We also updated the document to provide better illustration and better experiments. Now the code generates exactly the same results as shown in the paper.

1.1.0.0

The efficiency is optimized.

1.0.0.0

To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.