论文信息 - Neural Network Classification Using Error Entropy Minimization

Neural Network Classification Using Error Entropy Minimization

One way of using the entropy criteria in learning systems is to minimize the entropy of the error between two variables: typically, one is the output of the learning system and the other is the target. This framework has been used for regression. In this paper we show how to use the minimization of the entropy of the error for classification.

Luís A. Alexandre | Joaquim Marques de Sá | Jorge M. Santos

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