[W,V] = WEAKC(A,ALF,N,CLASSF)
WEAKC uses subsampled versions of A for training. Testing is done on the entire training set A. The best classifier is returned in W. VC combines all classifiers as a stacked combiner in VC.
This routine offers several ways to construct a wea classifier. The larger ALF, the larger ITER or the more complex CLASSF, the less weak the resulting classifier W will be. The combined classifier VC is for large values of N not a weak classifier.
For multi-class problem results may be improved in some cases, e.g. for small N and / or simple CLASSF, by W = A*(WEKAC*QDC(,,1e-6))