Lab 2: Updated and added figures

lab2/assignment1.R

@@ -38,6 +38,7 @@ lambda_with_k_features = function(x_train, y_train, alpha, k = 3) {
   fit_train <- glmnet(as.matrix(X_train), y_train, alpha = alpha)
   
   plot(fit_train, xvar = "lambda", label = TRUE)
+  grid()
   
   coef_matrix <- as.matrix(coef(fit_train))[-1, ] # Ignore intercept
   
@@ -65,6 +66,7 @@ print(lambda_with_3_features)
 fit <- cv.glmnet(as.matrix(X_train), y_train, alpha = 1) # Cross-validation
 
 plot(fit, xvar = "lambda", label = TRUE)
+grid()
 
 fit$lambda.min
 
@@ -77,6 +79,7 @@ plot(
   y_hat,
   xlab = "Observed test values",
   ylab = "Predicted test values",
-  main = "Original versus predicted test values ",
+  main = "Original vs. predicted test values ",
   col = "blue"
 )
+grid()