skopt.expected_minimum

skopt.expected_minimum(res, n_random_starts=20, random_state=None)

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:

resOptimizeResult, scipy object

The optimization result returned by a skopt minimizer.

n_random_startsint, default=20

The number of random starts for the minimization of the surrogate model.

random_stateint, RandomState instance, or None (default)

Set random state to something other than None for reproducible results.

Returns:

xlist

location of the minimum.

funfloat

the surrogate function value at the minimum.