Stability evaluation of Neural and statistical Classifiers based on Modified Semi-bounded Plug-in Algorithm

—This paper illustrates a new criterion for evaluating neural networks stability compared to the Bayesian classifier. The stability comparison is performed by the error rate probability densities estimation using the modified semi-bounded Plug-in algorithm. We attempt, in this work, to demonstrate that the Bayesian approach for neural networks improves the performance and stability degree of the classical neural classifiers.

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