Abstract
One of the most important research topics in machine learning is the problem of how to lower the generalization error of a learning algorithm, either by reducing the bias or the variance (or both). A major complication of any attempt to reduce variance or bias (or both) is that the definitions of “bias” and “variance” of a classification rule are not as obvious as they are in regression. In fact, there have been several conflicting suggestions for the bias-variance decomposition for classification problems.
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© 2013 Springer Science+Business Media New York
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Izenman, A.J. (2013). Committee Machines. In: Modern Multivariate Statistical Techniques. Springer Texts in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-0-387-78189-1_14
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DOI: https://doi.org/10.1007/978-0-387-78189-1_14
Publisher Name: Springer, New York, NY
Print ISBN: 978-0-387-78188-4
Online ISBN: 978-0-387-78189-1
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