PCA (Principial Component Analysis)

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Principal Component Analysis Implementation of LindsaySmithPCA.pdf
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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"

Cita come

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

Compatibilità della release di MATLAB
Creato con R2007b
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