The normalized sum of the sum of squares and products is given as:

The multi-class LDA method chooses the projections that maximize the ratio of the overall SSQP to the within class SSQP as shown:

This can be shown to correspond to the eigenvectors of which have the largest eigenvalues.

With this choice made, the p dimensional features thus obtained are uncorrelated.