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A regularization method for regression models that shrinks coefficients towards zero.
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Interpretation of lasso shrinkage
In the case of the ridge estimator, we can interpret the shrinkage induced by the ridge estimator to be at its most extreme when a predictor has low variance. High-variance predictors provide the most …