Classify handwritten digits using PCA. Use 200 digits for the train phase and 20 for the test.
I have no idea how PCA works as a classification method. I've learned to use it as a dimension reduction method where we subtract the original data from its mean, then we calculate the covariance matrix, eigenvalues and eigenvectors. From there, we're able to choose principal components and ignore the rest. How should I classify a bunch of handwritten digits? How to distinguish data from different classes? Or does it mean something totally different, that I must use PCA for feature extraction purposes and use a classification method afterwards?