Principal Component Analysis (PCA)
- This program uses Principal Component Analysis to reduce the number of features used in face recognition.
- This program allows you to set K if you know the number of Principal components needed or calculates K based on how much variance you would like to preserve in the images.
- The images consisting of reduced features can be used for training a neural network or logistic regression model.
- It decreases computation time of the program.
- Original & recovered images displayed
Citation pour cette source
Jason Rebello (2024). Principal Component Analysis (PCA) (https://www.mathworks.com/matlabcentral/fileexchange/42847-principal-component-analysis-pca), MATLAB Central File Exchange. Récupéré le .
Compatibilité avec les versions de MATLAB
Plateformes compatibles
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- AI, Data Science, and Statistics > Statistics and Machine Learning Toolbox > Dimensionality Reduction and Feature Extraction >
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PCA/
Version | Publié le | Notes de version | |
---|---|---|---|
1.0.0.0 |