Using prototypes to solve problems in neural net classifiers

It is shown that using the notion of 'prototype' in neural net classifiers can solve several problems that a nonlinear classifier might encounter. This has motivated the development of a new neural classifier named NNP. The author presents an empirical evaluation on the advantages of NNP over other classifiers.<
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