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, default=20) – The number of random starts for the minimization of the surrogate model.
random_state (int, RandomState instance, or None (default)) – Set random state to something other than None for reproducible results.
- Returns:
x (list) – location of the minimum.
fun (float) – the surrogate function value at the minimum.