MCLASSM

Computation of a combined, multi-class based mapping

   W = MCLASSM(A,MAPPING,MODE,PAR)
   W = A*MCLASSM([],MAPPING,MODE,PAR)
   W = A*MCLASSM(MAPPING,MODE,PAR)

Input
A	Dataset
MAPPING	Untrained mapping
MODE	Combining mode (optional; default: 'weight')
PAR	Parameter needed for the combining

Output
W	Combined mapping

Description

If A is a unlabeled dataset or double matrix, it is converted to a  one-class dataset. For one-class datasets A, the mapping is computed,  calling the untrained MAPPING using the labeled samples of A only.  For multi-class datasets separate mappings are determined for each class  in A. They are combined as defined by MODE and PAR. The following  combining rules are supported
'weight': weight the mapping outcome for class j by PAR(j) and sum  over the classes. This is useful for densities in which case  PAR is typically the set of class priors (these are in fact  the defaults if MODE = 'weight').

'mean'	combine by averaging.
'min'	combine by the minimum rule.
'max'	combine by the maximum rule.

This routine is only defined for datasets with crisp labels.

See also

datasets, mappings,