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Inclusion of additional constraints (typically a penalty for complexity) in the model fitting process. Used to prevent overfitting / enhance predictive accuracy.

13 votes
4 answers
3k views

Why do we need regularization for linear least squares given that a line is the simplest mod...

In short why do we need regularization for fitting a line to a data? … I understand that regularization improves generalization performance ie over unseen datasets and reduces over-fitting to training data. …
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