On the combination of supervised and unsupervised learning

Nathan Intrator

Physica A: Statistical Mechanics and its Applications, 1993, vol. 200, issue 1, 655-661

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.

Date: 1993
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:200:y:1993:i:1:p:655-661

DOI: 10.1016/0378-4371(93)90572-L

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