def check_min_samples_split(name):
    X, y = hastie_X, hastie_y
    ForestEstimator = FOREST_ESTIMATORS[name]

    # test boundary value
    assert_raises(ValueError,
                  ForestEstimator(min_samples_split=-1).fit, X, y)
    assert_raises(ValueError,
                  ForestEstimator(min_samples_split=0).fit, X, y)
    assert_raises(ValueError,
                  ForestEstimator(min_samples_split=1.1).fit, X, y)

    est = ForestEstimator(min_samples_split=10, n_estimators=1, random_state=0)
    est.fit(X, y)
    node_idx = est.estimators_[0].tree_.children_left != -1
    node_samples = est.estimators_[0].tree_.n_node_samples[node_idx]

    assert_greater(np.min(node_samples), len(X) * 0.5 - 1,
                   "Failed with {0}".format(name))

    est = ForestEstimator(min_samples_split=0.5, n_estimators=1, random_state=0)
    est.fit(X, y)
    node_idx = est.estimators_[0].tree_.children_left != -1
    node_samples = est.estimators_[0].tree_.n_node_samples[node_idx]

    assert_greater(np.min(node_samples), len(X) * 0.5 + 1,
                   "Failed with {0}".format(name))
dataset/ETHPy150Open scikit-learn/scikit-learn/sklearn/ensemble/tests/test_forest.py/check_min_samples_split/operator `-` -> `+`