Neural network classification: a Bayesian interpretation
- 1 January 1990
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Neural Networks
- Vol. 1 (4), 303-305
- https://doi.org/10.1109/72.80269
Abstract
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.Keywords
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- Parallel Distributed ProcessingPublished by MIT Press ,1986