Affiliation:
1. Foundation for Neural Networks, University of Nijmegen, 6525 EZ Nijmegen, The Netherlands
Abstract
The bias/variance decomposition of mean-squared error is well understood and relatively straightforward. In this note, a similar simple decomposition is derived, valid for any kind of error measure that, when using the appropriate probability model, can be derived from a Kullback-Leibler divergence or log-likelihood.
Subject
Cognitive Neuroscience,Arts and Humanities (miscellaneous)
Cited by
63 articles.
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