def test_dt_increase_acc(dummy_titanic):
    X_train, y_train, _, _ = dummy_titanic

    acc_list = []
    auc_list = []
    for depth in range(1, 10):
        dt = DecisionTree(depth_limit=depth)
        dt.fit(X_train, y_train)
        pred = dt.predict(X_train)
        pred_binary = np.round(pred)
        acc_list.append(accuracy_score(y_train, pred_binary))
        auc_list.append(roc_auc_score(y_train, pred))

    assert sorted(acc_list) == acc_list, 'Accuracy should increase as tree depth increases.'
    assert sorted(auc_list) == auc_list, 'AUC ROC should increase as tree depth increases.'