Machine Learning, Investment, AI, Sklearn, Quant.
accuracy = accuracy_score(y_test, y_pred) f1 = f1_score(y_test, y_pred) models.append(model) scores.append((accuracy, f1)) print(f'Fold Accuracy: {accuracy}, F1 Score: {f1}') # Select the best model based on F1 score best_index = np.argmax([score[1] for score in scores]) best_model =