Regulaization methods (1) 썸네일형 리스트형 [R] Regularization Methods : Binary 1. Regulaization Methods Regularization methods are based on a penalized likelihood : \(Q_{\lambda}(\beta_0, \beta) = -l(\beta_0, \beta) + p_{\lambda}(\beta)\) \((\hat{\beta_0}, \hat{\beta}) = arg min Q_{\lambda}(\beta_0, \beta)\) Penalized likelihood for quantitive Linear regression model : \(y_i = \beta_0 + x_i^T \beta + \epsilon_i\) l1-norm : \(\lambda \sum(\hat{\beta}^2)\) l2-norm : \(\lambd.. 이전 1 다음
