PCA (Principial Component Analysis)
Principal Component Analysis Implementation of LindsaySmithPCA.pdf
- 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 (2026). PCA (Principial Component Analysis) (https://ww2.mathworks.cn/matlabcentral/fileexchange/26793-pca-principial-component-analysis), MATLAB Central File Exchange. 检索时间: .
致谢
启发作品: EOF
