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Chapter 19: Cross-Validation and Estimates of Prediction Error

Chapter 19: Cross-Validation and Estimates of Prediction Error

pp. 751-772

Authors

, Saint Louis University, Missouri, , Virginia Polytechnic Institute and State University, , Arizona State University
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Summary

Overfitting refers to the use of a model with more parameters than can be justified by the data. Models that are overfit are often poor at predicting the outcome of new observations, that is, observations that were not used in the construction of the model. The next example illustrates this concept.

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