bayeso.acquisitions.gaussian_process_upper_confidence_bound

It defines a Gaussian process upper confidence bound acquisition function.

bayeso.acquisitions.gaussian_process_upper_confidence_bound.acq_fun(pred_mean: ndarray, pred_std: ndarray, Y_train: ndarray | None = None, kappa: float = 2.0, increase_kappa: bool = True) → ndarray

It is a Gaussian process upper confidence bound criterion.

Parameters:

  • pred_mean (numpy.ndarray) – posterior predictive mean function over X_test. Shape: (l, ).

  • pred_std (numpy.ndarray) – posterior predictive standard deviation function over X_test. Shape: (l, ).

  • Y_train (numpy.ndarray, optional) – outputs of X_train. Shape: (n, 1).

  • kappa (float, optional) – trade-off hyperparameter between exploration and exploitation.

  • increase_kappa (bool., optional) – flag for increasing a kappa value as Y_train grows. If Y_train is None, it is ignored, which means kappa is fixed.

Returns:

acquisition function values. Shape: (l, ).

Return type:

numpy.ndarray

Raises:

AssertionError