test_mondrian_partial_fit.py 文件源码

def test_min_samples_split():
    X_c, y_c = load_digits(return_X_y=True)
    X_r, y_r = make_regression(n_samples=10000, random_state=0)

    for mss in [2, 4, 10, 20]:
        mtr = MondrianTreeRegressor(random_state=0, min_samples_split=mss)
        mtr.partial_fit(X_r[: X_r.shape[0] // 2], y_r[: X_r.shape[0] // 2])
        mtr.partial_fit(X_r[X_r.shape[0] // 2:], y_r[X_r.shape[0] // 2:])
        n_node_samples = mtr.tree_.n_node_samples[mtr.tree_.children_left != -1]
        assert_greater(np.min(n_node_samples) + 1, mss)

        mtc = MondrianTreeClassifier(random_state=0, min_samples_split=mss)
        mtc.partial_fit(X_c[: X_c.shape[0] // 2], y_c[: X_c.shape[0] // 2])
        mtc.partial_fit(X_c[X_c.shape[0] // 2:], y_c[X_c.shape[0] // 2:])
        n_node_samples = mtc.tree_.n_node_samples[mtc.tree_.children_left != -1]
        assert_greater(np.min(n_node_samples) + 1, mss)