optuna.pruners

The pruners module defines a BasePruner class characterized by an abstract prune() method, which, for a given trial and its associated study, returns a boolean value representing whether the trial should be pruned. This determination is made based on stored intermediate values of the objective function, as previously reported for the trial using optuna.trial.Trial.report(). The remaining classes in this module represent child classes, inheriting from BasePruner, which implement different pruning strategies.

optuna.pruners.BasePruner	Base class for pruners.
optuna.pruners.MedianPruner	Pruner using the median stopping rule.
optuna.pruners.NopPruner	Pruner which never prunes trials.
optuna.pruners.PercentilePruner	Pruner to keep the specified percentile of the trials.
optuna.pruners.SuccessiveHalvingPruner	Pruner using Asynchronous Successive Halving Algorithm.
optuna.pruners.HyperbandPruner	Pruner using Hyperband.
optuna.pruners.ThresholdPruner	Pruner to detect outlying metrics of the trials.