def test_rf_better_than_dt(dummy_titanic):
    X_train, y_train, X_test, y_test = dummy_titanic

    dt = DecisionTree(depth_limit=10)
    dt.fit(X_train, y_train)

    rf = RandomForest(depth_limit=10, num_trees=7, col_subsampling=0.8, row_subsampling=0.8)
    rf.fit(X_train, y_train)

    pred_test_dt = dt.predict(X_test)
    pred_test_binary_dt = np.round(pred_test_dt)
    acc_test_dt = accuracy_score(y_test, pred_test_binary_dt)
    auc_test_dt = roc_auc_score(y_test, pred_test_dt)

    pred_test_rf = rf.predict(X_test)
    pred_test_binary_rf = np.round(pred_test_rf)
    acc_test_rf = accuracy_score(y_test, pred_test_binary_rf)
    auc_test_rf = roc_auc_score(y_test, pred_test_rf)

    assert acc_test_rf > acc_test_dt, 'RandomForest should have higher accuracy than DecisionTree on test set.'
    assert auc_test_rf > auc_test_dt, 'RandomForest should have higher AUC ROC than DecisionTree on test set.'