In the last years, great attention has been devoted to multiple classifier systems. The implementation of such a system implies the definition of a rule (combining rule) for determining the most likely class, on the basis of the class attributed by each single expert. The availability of a criterion to evaluate the credibility of the decision taken by a classifier can be profitable in order to implement the combining rule. We propose a method that, after defining the reliability of a classification on the basis of information directly derived from the output of the classifier, uses this information in the context of a combining rule. The results obtained by combining four handwritten character on the basis of classification reliability are compared with those obtained by using three different combining criteria. Tests have been performed using a standard handwritten character database.
Classification reliability and its use in multi-classifier systems
TORTORELLA, Francesco;
1997-01-01
Abstract
In the last years, great attention has been devoted to multiple classifier systems. The implementation of such a system implies the definition of a rule (combining rule) for determining the most likely class, on the basis of the class attributed by each single expert. The availability of a criterion to evaluate the credibility of the decision taken by a classifier can be profitable in order to implement the combining rule. We propose a method that, after defining the reliability of a classification on the basis of information directly derived from the output of the classifier, uses this information in the context of a combining rule. The results obtained by combining four handwritten character on the basis of classification reliability are compared with those obtained by using three different combining criteria. Tests have been performed using a standard handwritten character database.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
