A Method for Error Rejection in Multiple Classifier Systems

In the literature, the introduction of the reject option inMultiple Classifier Systems has been analysed only fromthe experimental point of view. Following a firsttheoretical analysis provided by the authors, in thispaper, we analyse, in the framework of the minimum risktheory, the problem of finding the best error-reject tradeoffachievable by a linear combination of a given set oftrained classifiers. An algorithm for computing theparameters of the linear combination and of the rejectrule is then proposed. Experimental results on two datasets of remote-sensing images are reported.