how can I simplify the follwoing for faster run: C_grid_linear <- c(0.1, 1, 10)
best_lin <- NULL; best_lin_auc <- -Inf
for (C_val in C_grid_linear) {
svm_lin <- svm(y ~ ., data = train_bank_data, kernel = "linear", cost = C_val, probability = TRUE)
pred <- predict(svm_lin, test_bank_data, probability = TRUE)
probs <- attr(pred, "probabilities")[, "yes"]
metrics <- eval_model(test_bank_data$y, factor(pred, levels = c("no", "yes")), probs)
if (metrics$AUC > best_lin_auc) { best_lin <- list(C = C_val, metrics = metrics); best_lin_auc <- metrics$AUC }