Neural network classification: a Bayesian interpretation.
The relationship between minimizing a mean squared error and finding the optimal Bayesian classifier is reviewed. This provides a theoretical interpretation for the process by which neural networks are used in classification. A number of confidence measures are proposed to evaluate the performance of the neural network classifier within a statistical framework.
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Dept. of Electr. Eng., Stanford Univ., CA.