deephyper.skopt.optimizer.optimizer#

Functions

boltzmann_distribution

check_x_in_space

cook_estimator

Cook a default estimator.

cook_initial_point_generator

Cook a default initial point generator.

cook_objective_scaler

Prepare a Scikit-Learn preprocessing pipeline to map the output objective to a different space.

create_result

Initialize an OptimizeResult object.

gaussian_acquisition_1D

A wrapper around the acquisition function that is called by fmin_l_bfgs_b.

has_gradients

Check if an estimator's predict method provides gradients.

is_2Dlistlike

is_listlike

log

Return the logarithm of x to the given base.

normalize_dimensions

Create a Space where all dimensions are normalized to unit range.

Classes

Categorical

Search space dimension that can take on categorical values.

MoScalarFunction

Abstract class representing a scalarizing function.

Optimizer

Run bayesian optimisation loop in DeepHyper.

Space

Initialize a search space from given specifications.

Exceptions

ExhaustedFailures

Raised when the search has seen max_failures failures without any valid objective value.

ExhaustedSearchSpace

"Raised when the search cannot sample new points from the ConfigSpace.