deephyper.skopt.optimizer.optimizer

Sickit-Optimize optimizer class.

Functions

boltzmann_distribution	Boltzmann distribution function.
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 transform the objective.
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_failure	Test if the input value is a failure.
is_listlike
is_not_improving	Check if scores have improved over 'patience' length.
log	log(x, [base=math.e]) 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.
GaussianProcessRegressor	GaussianProcessRegressor that allows noise tunability.
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 search has seen max_total_failures failures for the entire search.
ExhaustedSearchSpace	Raised when the search cannot sample new points from the ConfigSpace.