046f68ada873c5c02d17d49dac1f81c9c7a4179b,skopt/tree_opt.py,,gbrt_minimize,#,111

Before Change

        base_estimator = GradientBoostingQuantileRegressor(base_estimator=gbrt,
                                                           random_state=rng)

    return _tree_minimize(func, dimensions, base_estimator,
                          n_calls=n_calls,
                          n_points=n_points, n_random_starts=n_random_starts,
                          x0=x0, y0=y0, random_state=random_state, xi=xi,
                          kappa=kappa, acq=acq)


def forest_minimize(func, dimensions, base_estimator="et", n_calls=100,
                    n_points=100, n_random_starts=10, x0=None, y0=None,

After Change

        base_estimator = GradientBoostingQuantileRegressor(base_estimator=gbrt,
                                                           random_state=rng)

    res = _tree_minimize(func, dimensions, base_estimator,
                         n_calls=n_calls,
                         n_points=n_points, n_random_starts=n_random_starts,
                         x0=x0, y0=y0, random_state=random_state, xi=xi,
                         kappa=kappa, acq=acq)
    res.specs = specs

    return res


def forest_minimize(func, dimensions, base_estimator="et", n_calls=100,
                    n_points=100, n_random_starts=10, x0=None, y0=None,

Instances