Feature Extraction

Fisher Criterion is basically projecting into a 1D line for separability. The solution is

which we gets from maximizing

We can generalize this. If we have separability criteria , all the criteria can be mazimized by using eigenvectors corresponding to the largest eigenvalues of . Hence, the feature extraction matrix

contains the top eigenvectors.

It is a good time to introduce Karhunen-Loeve Transform