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Do principal components analysis (PCA) on real-valued data.
Two methods are available: 'eig' and 'svd' which solve the problem by eigenvalue decomposition and singula value decomposition, respectively. Please note that 'svd' is running in 'economy' mode.
Cite As
Siqing Wu (2026). Principal components analysis (PCA) (https://www.mathworks.com/matlabcentral/fileexchange/20898-principal-components-analysis-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 (1.31 KB)
-
No License
MATLAB Release Compatibility
- Compatible with any release
Platform Compatibility
- Windows
- macOS
- Linux
| Version | Published | Release Notes | Action |
|---|---|---|---|
| 1.0.0.0 | One line of testing code was not deleted in the first version. |
