deephyper.skopt.utils

Functions

check_dimension_names	Check whether all dimensions have names.
check_list_types	Check whether all elements of a list x are of the correct type(s) and raise a ValueError if they are not.
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.
deepcopy	Deep copy operation on arbitrary Python objects.
dimensions_aslist	Convert a dict representation of a search space into a list of dimensions, ordered by sorted(search_space.keys()).
dump	Store an skopt optimization result into a file.
eval_callbacks	Evaluate list of callbacks on result.
expected_minimum	Compute the minimum over the predictions of the last surrogate model.
expected_minimum_random_sampling	Minimum search by doing naive random sampling, Returns the parameters that gave the minimum function value.
has_gradients	Check if an estimator's predict method provides gradients.
is_2Dlistlike
is_listlike
load	Reconstruct a skopt optimization result from a file persisted with deephyper.skopt.dump.
normalize_dimensions	Create a Space where all dimensions are normalized to unit range.
point_asdict	Convert the list representation of a point from a search space to the dictionary representation, where keys are dimension names and values are corresponding to the values of dimensions in the list.
point_aslist	Convert a dictionary representation of a point from a search space to the list representation.
use_named_args	Wrapper / decorator for an objective function that uses named arguments to make it compatible with optimizers that use a single list of parameters.
wraps	Decorator factory to apply update_wrapper() to a wrapper function

Classes

Dimension	Base class for search space dimensions.
ExtraTreesRegressor	ExtraTreesRegressor that supports conditional standard deviation.
GradientBoostingQuantileRegressor	Predict several quantiles with one estimator.
Grid	Generate samples from a regular grid.
Halton	Creates Halton sequence samples.
Hammersly	Creates Hammersley sequence samples.
InitialPointGenerator
Lhs	Latin hypercube sampling
OrderedDict	Dictionary that remembers insertion order
RandomForestRegressor	RandomForestRegressor that supports conditional std computation.
Sobol	Generates a new quasirandom Sobol' vector with each call.
Space	Initialize a search space from given specifications.