Built-In

BoTorch Sampler

Class or Function Names BoTorchSampler Installation pip install optuna-integration botorch Example from optuna_integration import BoTorchSampler sampler = BoTorchSampler() Others See the documentation for more details.

Brute Force Search

Class or Function Names BruteForceSampler Example import optuna from optuna.samplers import BruteForceSampler def objective(trial): x = trial.suggest_float("x", -5, 5) return x**2 sampler = BruteForceSampler() study = optuna.create_study(sampler=sampler) study.optimize(objective, n_trials=10) Others See the documentation for more details.

CMA-ES Sampler

Class or Function Names CmaEsSampler Installation pip install cmaes Example import optuna from optuna.samplers import CmaEsSampler def objective(trial): x = trial.suggest_float("x", -1, 1) y = trial.suggest_int("y", -1, 1) return x**2 + y sampler = CmaEsSampler() study = optuna.create_study(sampler=sampler) study.optimize(objective, n_trials=20) Others See the documentation for more details.

Contour Plot

Class or Function Names plot_contour Example from optuna.visualization import plot_contour plot_contour(study) Others See the documentation for more details.

Empirical Distribution Function Plot

Class or Function Names plot_edf Example from optuna.visualization import plot_edf plot_edf(study) Others See the documentation for more details.

Gaussian Process-Based Sampler

Class or Function Names GPSampler Installation pip install scipy torch Example import optuna from optuna.samplers import GPSampler def objective(trial): x = trial.suggest_float("x", -5, 5) return x**2 sampler = GPSampler() study = optuna.create_study(sampler=sampler) study.optimize(objective, n_trials=100) Others See the documentation for more details.

Grid Search

Class or Function Names GridSampler Example import optuna from optuna.samplers import GridSampler def objective(trial): x = trial.suggest_float("x", -100, 100) y = trial.suggest_int("y", -100, 100) return x**2 + y**2 search_space = {"x": [-50, 0, 50], "y": [-99, 0, 99]} sampler = GridSampler(search_space) study = optuna.create_study(sampler=sampler) study.optimize(objective) Others See the documentation for more details.

Hyperband Pruner

Class or Function Names HyperbandPruner Example study = optuna.create_study( direction="maximize", pruner=optuna.pruners.HyperbandPruner( min_resource=1, max_resource=n_train_iter, reduction_factor=3 ), ) study.optimize(objective, n_trials=20) See example.py for a full example. Others See the documentation for more details.

Hyperparameter Importances Plot

Class or Function Names plot_param_importances Example from optuna.visualization import plot_param_importances plot_param_importances(study) Others See the documentation for more details.

Hypervolume History Plot

Class or Function Names plot_hypervolume_history Example from optuna.visualization import plot_hypervolume_history plot_hypervolume_history(study, reference_point) Others See the documentation for more details.

Intermediate Values Plot

Class or Function Names plot_intermediate_values Example from optuna.visualization import plot_intermediate_values plot_intermediate_values(study) Others See the documentation for more details.

Median Pruner

Class or Function Names MedianPruner Example import optuna from optuna.pruners import MedianPruner def objective(trial): s = 0 for step in range(20): x = trial.suggest_float(f"x_{step}", -5, 5) s += x**2 trial.report(s, step) if trial.should_prune(): raise optuna.TrialPruned() return s pruner = MedianPruner() study = optuna.create_study(pruner=pruner) study.optimize(objective, n_trials=20) Others See the documentation for more details.

Nop Pruner

Class or Function Names NopPruner Example study = optuna.create_study(direction="maximize", pruner=optuna.pruners.NopPruner()) study.optimize(objective, n_trials=20) See example.py for a full example. Others See the documentation for more details.

NSGAII Search

Class or Function Names NSGAIISampler Example import optuna from optuna.samplers import NSGAIISampler def objective(trial): x = trial.suggest_float("x", -5, 5) return x**2 sampler = NSGAIISampler() study = optuna.create_study(sampler=sampler) study.optimize(objective, n_trials=10) Others See the documentation for more details.

NSGAIII Search

Class or Function Names NSGAIIISampler Example import optuna from optuna.samplers import NSGAIIISampler def objective(trial): x = trial.suggest_float("x", -5, 5) return x**2 sampler = NSGAIIISampler() study = optuna.create_study(sampler=sampler) study.optimize(objective, n_trials=10) Others See the documentation for more details.

Optimization History Plot

Class or Function Names plot_optimization_history Example from optuna.visualization import plot_optimization_history plot_optimization_history(study) Others See the documentation for more details.

Parallel Coordinate Plot

Class or Function Names plot_parallel_coordinate Example from optuna.visualization import plot_parallel_coordinate plot_parallel_coordinate(study) Others See the documentation for more details.

Pareto-front Plot

Class or Function Names plot_pareto_front Example from optuna.visualization import plot_pareto_front plot_pareto_front(study) Others See the documentation for more details.

Partial Fixed Sampler

Class or Function Names PartialFixedSampler Example import optuna from optuna.samplers import PartialFixedSampler def objective(trial): x = trial.suggest_float("x", -1, 1) y = trial.suggest_int("y", -1, 1) return x**2 + y tpe_sampler = optuna.samplers.TPESampler() fixed_params = {"y": 0} partial_sampler = PartialFixedSampler(fixed_params, tpe_sampler) study = optuna.create_study(sampler=partial_sampler) study.optimize(objective, n_trials=10) Others See the documentation for more details.

Patient Pruner

Class or Function Names PatientPruner Example study = optuna.create_study( direction="maximize", pruner=optuna.pruners.PatientPruner(optuna.pruners.MedianPruner(), patience=1), ) study.optimize(objective, n_trials=20) See example.py for a full example. Others See the documentation for more details.

Percentile Pruner

Class or Function Names PercentilePruner Example import optuna from optuna.pruners import PercentilePruner def objective(trial): s = 0 for step in range(20): x = trial.suggest_float(f"x_{step}", -5, 5) s += x**2 trial.report(s, step) if trial.should_prune(): raise optuna.TrialPruned() return s pruner = PercentilePruner(25.0) study = optuna.create_study(pruner=pruner) study.optimize(objective, n_trials=20) Others See the documentation for more details.

PyCMA Sampler

Class or Function Names PyCmaSampler Installation pip install optuna-integration cma Example from optuna_integration import PyCmaSampler sampler = PyCmaSampler() Others See the documentation for more details.

QMC Search

Class or Function Names QMCSampler Example import optuna from optuna.samplers import QMCSampler def objective(trial): x = trial.suggest_float("x", -5, 5) return x**2 sampler = QMCSampler() study = optuna.create_study(sampler=sampler) study.optimize(objective, n_trials=10) Others See the documentation for more details.

Random Search

Class or Function Names RandomSampler Example import optuna from optuna.samplers import RandomSampler def objective(trial): x = trial.suggest_float("x", -5, 5) return x**2 sampler = RandomSampler() study = optuna.create_study(sampler=sampler) study.optimize(objective, n_trials=10) Others See the documentation for more details.

Rank Plot

Class or Function Names plot_rank Example from optuna.visualization import plot_rank plot_rank(study) Others See the documentation for more details.

Slice Plot

Class or Function Names plot_slice Example from optuna.visualization import plot_slice plot_slice(study) Others See the documentation for more details.

Successive Halving Pruner

Class or Function Names SuccessiveHalvingPruner Example study = optuna.create_study( direction="maximize", pruner=optuna.pruners.SuccessiveHalvingPruner() ) study.optimize(objective, n_trials=20) See example.py for a full example. Others See the documentation for more details.

Terminator Improvement Plot

Class or Function Names plot_terminator_improvement Example from optuna.visualization import plot_terminator_improvement plot_terminator_improvement(study) Others See the documentation for more details.

Threshold Pruner

Class or Function Names ThresholdPruner Example study = create_study(pruner=ThresholdPruner(upper=1.0)) study.optimize(objective_for_upper, n_trials=10) study = create_study(pruner=ThresholdPruner(lower=0.0)) study.optimize(objective_for_lower, n_trials=10) See example.py for a full example. Others See the documentation for more details.

Timeline Plot

Class or Function Names plot_timeline Example from optuna.visualization import plot_timeline plot_timeline(study) Others See the documentation for more details.

TPE Sampler

Class or Function Names TPESampler Example import optuna from optuna.samplers import TPESampler def objective(trial): x = trial.suggest_float("x", -10, 10) return x**2 sampler = TPESampler() study = optuna.create_study(sampler=sampler) study.optimize(objective, n_trials=10) Others See the documentation for more details.

Wilcoxon Pruner

Class or Function Names WilcoxonPruner Example study = optuna.create_study(pruner=optuna.pruners.WilcoxonPruner(p_threshold=0.1)) study.optimize(objective, n_trials=100) See example.py for a full example. Others See the documentation for more details.