def METHOD_NAME():
    X, y = iris_data()
    X_train, X_test, y_train, y_test = train_test_split(
        X, y, test_size=0.3, random_state=123, shuffle=True, stratify=y
    )
    tree = DecisionTreeClassifier(random_state=123)
    avg_expected_loss, avg_bias, avg_var = bias_variance_decomp(
        tree, X_train, y_train, X_test, y_test, loss="0-1_loss", random_seed=123
    )
    assert round(avg_expected_loss, 3) == 0.062
    assert round(avg_bias, 3) == 0.022
    assert round(avg_var, 3) == 0.040