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rid of irrelevant features but rather minimize their impact on the trained model. Lasso method Lasso is another extension built on regularized linear regression, but with a small twist. The loss function of Lasso is in the form: L = ∑( Ŷi- Yi)2 + λ∑ |β| The only difference from Ridge regression is