Principal components analysis (PCA)
Version 1.0.0.0 (1.31 KB) by
Siqing Wu
Principal components analysis (PCA)
4.5K Downloads
Updated
31 Jul 2008
No License
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 (2024). Principal components analysis (PCA) (https://www.mathworks.com/matlabcentral/fileexchange/20898-principal-components-analysis-pca), MATLAB Central File Exchange. Retrieved .
MATLAB Release Compatibility
Created with
R2007a
Compatible with any release
Platform Compatibility
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- AI, Data Science, and Statistics > Statistics and Machine Learning Toolbox > Dimensionality Reduction and Feature Extraction >
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Version | Published | Release Notes | |
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1.0.0.0 | One line of testing code was not deleted in the first version. |