Confidence in prediction by neural networks
Liat Ein‐Dor, Ido Kanter · Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics · 1999
The idea that a trained network can assign a confidence number to its prediction, indicating the level of its reliability, is addressed and exemplified by an analytical examination of a perceptron with discrete and continuous output units. Results are derived for both Gibbs and Bayes scenarios. The information gain by the confidence number is estimated by various entropy measurements.