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Neural network classification: a Bayesian interpretation

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1 Author(s)
Wan, E.A. ; Dept. of Electr. Eng., Stanford Univ., CA, USA

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

Published in:

Neural Networks, IEEE Transactions on  (Volume:1 ,  Issue: 4 )