PCA performs eigenvalue decomposition and reduces dimensions whilst preserving information by maximising the varaince of the components
Eigenfaces is a facial identification problem LFW dataset and the model must predict the names for the faces based on the SVM(Support Vector Machine) classifier which receives an input whose dimensions are reduced using PCA (from 1850 to 150).
- Here are the results for a few of them:
