def METHOD_NAME():
    from sklearn.metrics import f1_score
    lr = LogisticRegression(solver="liblinear", multi_class="ovr")
    scores = bootstrap_point632_score(
        lr, X[:100], y[:100], scoring_func=f1_score, random_seed=123
    )
    f1 = np.mean(scores)
    assert len(scores == 200)
    assert np.round(f1, 2) == 1.0, f1