Probabilistic PCA and Factor Analysis
EM algorithm for fitting PCA and FA model. This is probabilistic treatment of dimensional reduction.
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This package provides several functions that mainly use EM algorithm to fit probabilistic PCA and Factor analysis models.
PPCA is probabilistic counterpart of PCA model. PPCA has the advantage that it can be further extended to more advanced model, such as mixture of PPCA, Bayeisan PPCA or model dealing with missing data, etc. However, this package mainly served a research and teaching purpose for people to understand the model. The code is succinct so that it is easy to read and learn.
This package is now a part of the PRML toolbox (http://cn.mathworks.com/help/stats/ppca.html).
Cite As
Mo Chen (2026). Probabilistic PCA and Factor Analysis (https://uk.mathworks.com/matlabcentral/fileexchange/55883-probabilistic-pca-and-factor-analysis), MATLAB Central File Exchange. Retrieved .
Acknowledgements
Inspired by: Pattern Recognition and Machine Learning Toolbox
General Information
- Version 1.0.0.0 (5.13 KB)
MATLAB Release Compatibility
- Compatible with any release
Platform Compatibility
- Windows
- macOS
- Linux
| Version | Published | Release Notes | Action |
|---|---|---|---|
| 1.0.0.0 |
update description
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