Abstract
The first three examples described in Chapter 1 have several components in common. For each there is a set of variables that might be denoted as inputs, which are measured or preset. These have some influence on one or more outputs. For each example the goal is to use the inputs to predict the values of the outputs. This exercise is called supervised learning.
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© 2001 Springer Science+Business Media New York
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Hastie, T., Friedman, J., Tibshirani, R. (2001). Overview of Supervised Learning. In: The Elements of Statistical Learning. Springer Series in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-0-387-21606-5_2
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DOI: https://doi.org/10.1007/978-0-387-21606-5_2
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