QUADRC

Quadratic Discriminant Classifier

    W = QUADRC(A,R,S)

Input
A	Dataset
R,S	0 <= R,S <= 1, regularization parameters (default: R = 0, S = 0)

Output
W	Quadratic Discriminant Classifier mapping

Description

Computation of the quadratic classifier between the classes of the dataset  A assuming normal densities. R and S are regularization parameters used  for finding the covariance matrix as

      G = (1-R-S)*G + R*diag(diag(G)) + S*mean(diag(G))*eye(size(G,1))

NOTE This routine differs from QDC; instead of using the densities, it is based  on the class covariances. The multi-class problem is solved by multiple  two-class quadratic discriminants. It is, thereby, a quadratic equivalent  of FISHERC.

See also

mappings, datasets, fisherc, nmc, nmsc, ldc, udc, qdc,