deephyper.skopt.utils.expected_minimum_random_sampling

deephyper.skopt.utils.expected_minimum_random_sampling#

deephyper.skopt.utils.expected_minimum_random_sampling(res, n_random_starts=100000, random_state=None)[source]#

Minimum search by doing naive random sampling.

Returns the parameters that gave the minimum function value. Can be used 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

  • 100000. (model. Defaults to)

  • 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)

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