School of Mathematical Sciences, Tel-Aviv University, Ramat-Aviv 69978, Israel
Abstract:
The bias/variance dilemma is addressed in the context of neural networks. A bias constraint based on prior knowledge about the underlying distribution of the data is discussed as a means for reducing the overall error measure of a classifier.