246339ce01898c92ce9e143895c5def9c46dcb78,skopt/gp_opt.py,,gp_minimize,#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#,26

Before Change


    rng = check_random_state(random_state)

    // Bounds
    n_params = len(bounds)
    lb, ub = extract_bounds(bounds)

    // Default GP
    if base_estimator is None:

After Change


        models.append(gp)

        if search == "sampling":
            X = space.transform(space.rvs(n_samples=n_points,
                                          random_state=rng))
            values = _gaussian_acquisition(
                X=X, model=gp,  y_opt=np.min(yi), method=acq,
                xi=xi, kappa=kappa)
            next_x = X[np.argmin(values)]
Italian Trulli
In pattern: SUPERPATTERN

Frequency: 3

Non-data size: 4

Instances


Project Name: scikit-optimize/scikit-optimize
Commit Name: 246339ce01898c92ce9e143895c5def9c46dcb78
Time: 2016-06-14
Author: g.louppe@gmail.com
File Name: skopt/gp_opt.py
Class Name:
Method Name: gp_minimize


Project Name: scikit-optimize/scikit-optimize
Commit Name: 246339ce01898c92ce9e143895c5def9c46dcb78
Time: 2016-06-14
Author: g.louppe@gmail.com
File Name: skopt/dummy_opt.py
Class Name:
Method Name: dummy_minimize


Project Name: pymc-devs/pymc3
Commit Name: a3c20606753726e09799f05721e68101e637df72
Time: 2021-01-19
Author: aloctavodia@gmail.com
File Name: pymc3/distributions/bart.py
Class Name: BaseBART
Method Name: grow_tree