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Regularization parameter λ affects the weights (features) we learned in both Ridge regression (left) and LASSO regression (right) on the Diabetes dataset. Curves with different colors correspond to different wi’s (features). Notice LASSO, unlike Ridge, sets feature weights to zero leading to sparsity. See Notebook 3.
