optuna.samplers¶

The samplers module defines a base class for parameter sampling as described extensively in BaseSampler. The remaining classes in this module represent child classes, deriving from BaseSampler, which implement different sampling strategies.

`optuna.samplers.BaseSampler`	Base class for samplers.
`optuna.samplers.GridSampler`	Sampler using grid search.
`optuna.samplers.RandomSampler`	Sampler using random sampling.
`optuna.samplers.TPESampler`	Sampler using TPE (Tree-structured Parzen Estimator) algorithm.
`optuna.samplers.CmaEsSampler`	A sampler using cmaes as the backend.
`optuna.samplers.PartialFixedSampler`	Sampler with partially fixed parameters.
`optuna.samplers.NSGAIISampler`	Multi-objective sampler using the NSGA-II algorithm.
`optuna.samplers.MOTPESampler`	Multi-objective sampler using the MOTPE algorithm.
`optuna.samplers.IntersectionSearchSpace`	A class to calculate the intersection search space of a `BaseStudy`.
`optuna.samplers.intersection_search_space`	Return the intersection search space of the `BaseStudy`.