In the literature, the introduction of the reject option in multiple classifier systems has been analysed only from the experimental point of view. Following a first theoretical analysis provided by the authors, we analyse, within the framework of the minimum risk theory, the problem of finding the best error-reject trade-off achievable by a linear combination of a given set of trained classifiers. An algorithm for computing the parameters of the linear combination and of the reject rule is then proposed. Experimental results on two data sets of remote-sensing images are reported.


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    Title :

    A method for error rejection in multiple classifier systems


    Contributors:
    Fumera, G. (author) / Roli, F. (author) / Vernazza, G. (author)


    Publication date :

    2001-01-01


    Size :

    472658 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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