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É um assunto batido, mas sempre vale uma rápida revisão.

Um trecho: “[…]To generalize, a model that overfits its training set has low bias but high variance – it predicts the targets in the training set very accurately, but any slight changes to the predictors would result in vastly different predictions for the targets.
Overfitting differs from multicollinearity, which I will explain in later post. Overfitting has irrelevant predictors, whereas multicollinearity has redundant predictors.

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