Class-contrastive trace maximization

Learns a k-dimensional subspace whose closed-form solution is the leading eigenvectors of a signed combination of within-class scatter matrices - maximizing projected variance for a target class while jointly minimizing it for all other classes - generalizing single-class PCA and the Fukunaga-Koontz transform to more than two classes in one eigendecomposition.