SDCOMBINE Fixed classifier combiner PC=SDCOMBINE(PS,RULE) crisp combiner: PC=SDCOMBINE([P1 P2 ...],RULE) soft output combiner: PC=SDCOMBINE([-P1 -P2 ...],RULE) INPUT PS Stack pipeline (constructed by SDSTACK or concatenation []) RULE String fusion rule on soft ouptus: 'mean' (default),'prod','min','max' on crisp outputs: 'all agree' or 'at least' P1,P2 Classifier pipelines OUTPUT PC Combiner pipeline OPTIONS 'mean','prod','max','min' - fixed combiner type is PS returns soft outputs 'all agree' - crisp combining rule 'at least',N - crisp combining, (default N is number of classifiers) 'target',NAME - name of target class for 'at least' rule 'reject',NAME - name of reject decision for crisp rules (def:'reject') DESCRIPTION SDCOMBINE adds fixed combination step to a stack pipeline with multiple classifiers. If the pipelines return soft outputs, mean, prod, min and max rules can be used. Crisp decision combining is possible with: 'all agree' rule: if all classifiers agree, this class, otherwise 'reject' 'at least' rule: target class must be defined. If at least N classifiers votes for the target, it's target, otherwise reject EXAMPLES SOFT outputs combining: p1=sdlinear(a); p2=sdnorm( -sdparzen(a) ) % so that both return posteriors pc=sdcombine([-p1 -p2],'prod'); CRISP decision combiner: p1=sdgauss(a); p2=sdparzen(a); % classifiers return decisions by default -> crisp pc=sdcombine([p1 p2],'all agree'); pc2=sdcombine([p1 p2],'at least',1,'target','apple'); SEE ALSO SDSTACK