PCA (Principial Component Analysis)

版本 1.2.0.0 (1.5 KB) 作者: Andreas
Principal Component Analysis Implementation of LindsaySmithPCA.pdf
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更新时间 2010/3/18

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- Subtracting the mean of the data from the original dataset
- Finding the covariance matrix of the dataset
- Finding the eigenvector(s) associated with the greatest eigenvalue(s)
- Projecting the original dataset on the eigenvector(s)
- Use only a certain number of the eigenvector(s)
- Do back-project to the original basis vectors

Implementation of
http://www.cs.otago.ac.nz/cosc453/student_tutorials/principal_components.pdf

"A tutorial on Principial Component Analysis"

引用格式

Andreas (2024). PCA (Principial Component Analysis) (https://www.mathworks.com/matlabcentral/fileexchange/26793-pca-principial-component-analysis), MATLAB Central File Exchange. 检索时间: .

MATLAB 版本兼容性
创建方式 R2007b
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在 Help Center 和 MATLAB Answers 中查找有关 Dimensionality Reduction and Feature Extraction 的更多信息
致谢

启发作品: EOF

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