LASSO (1) 썸네일형 리스트형 [R] Variable Selection Methods : Lasso 1. Lasso Regression Ridge have disadvantages of including all p predictors in the final model. What we want to do is variable selection. Lasso shrinks \(\hat{\beta}\) towards zero. \(RSS + \lambda\sum_{j=1}^{p}|\beta_j|\) The \(l_1\)-norm of \(\hat{\beta}\) : \(df(\hat{\beta}_{\lambda_1}) = 0 이전 1 다음
