# 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.