Abstract
For most of this book, the fitting (learning) of models has been achieved by minimizing a sum of squares for regression, or by minimizing cross-entropy for classification. In fact, both of these minimizations are instances of the maximum likelihood approach to fitting.
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© 2001 Springer Science+Business Media New York
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Hastie, T., Friedman, J., Tibshirani, R. (2001). Model Inference and Averaging. In: The Elements of Statistical Learning. Springer Series in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-0-387-21606-5_8
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DOI: https://doi.org/10.1007/978-0-387-21606-5_8
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4899-0519-2
Online ISBN: 978-0-387-21606-5
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