stepwiseとlasso回帰における変数選択を比較 - Qiita> model.rg <- glm(Y.train~., data = X.train) > step.result<-step(model.rg) "略" > step.result Call: glm(formula = Y.train ~ X1 + X2 + X3 + X4 + X5 + X6 + X7 + X13 + X18 + X20, data = X.train) Coefficients: (Intercept) X1 X2 X3 X4 X5 X6 2.87439 0.67332 -0.42552 0.29593 -0.90412 0.50839 0.64421 X7 X13 X18 X20 -0.03680 0.05682 0.02724 0.02971 Degrees of Freedom: 799 Total (i.e. Null); 789 Residual Nul
