HyperParameterSampling class

Definition

Abstract base class for all hyperparameter sampling algorithms.

This class encapsulates the hyperparameter space, the sampling method, and additional properties for derived sampling classes: BayesianParameterSampling, GridParameterSampling, and RandomParameterSampling.

HyperParameterSampling(sampling_method_name, parameter_space, properties=None, supported_distributions=None, distributions_validators=None)
Inheritance
builtins.object
HyperParameterSampling

Parameters

sampling_method_name
str

The name of the sampling method.

parameter_space
dict

A dictionary containing each parameter and its distribution.

properties
dict

A dictionary with additional properties for the algorithm.

supported_distributions
set[str]

A list of the supported distribution methods. The default None indicates all distributions are supported as described in module parameter_expressions.

Methods

to_json()

Return the JSON of the hyperparameter sampling object.

to_json()

Return the JSON of the hyperparameter sampling object.

to_json()

Returns

JSON formatted sampling policy.

Return type

str