deephyper.skopt.expected_minimum

deephyper.skopt.expected_minimum#

deephyper.skopt.expected_minimum(res, n_random_starts=20, random_state=None)[source]#

Compute the minimum over the predictions of the last surrogate model.

Uses expected_minimum_random_sampling with n_random_starts = 100000, when the space contains any categorical values.

Note

The returned minimum may not necessarily be an accurate prediction of the minimum of the true objective function.

Parameters:
  • res (OptimizeResult scipy object) – The optimization result returned by a skopt minimizer.

  • n_random_starts (int) – The number of random starts for the minimization of the surrogate model. Defaults to 20.

  • random_state (int or RandomState, Optional) – Set random state to something other than None for reproducible results.

Returns:

location of the minimum. fun (float): the surrogate function value at the minimum.

Return type:

x (list)