optuna.visualization.plot_optimization_history¶
-
optuna.visualization.
plot_optimization_history
(study, *, target=None, target_name='Objective Value')[source]¶ Plot optimization history of all trials in a study.
Example
The following code snippet shows how to plot optimization history.
import optuna def objective(trial): x = trial.suggest_float("x", -100, 100) y = trial.suggest_categorical("y", [-1, 0, 1]) return x ** 2 + y sampler = optuna.samplers.TPESampler(seed=10) study = optuna.create_study(sampler=sampler) study.optimize(objective, n_trials=10) fig = optuna.visualization.plot_optimization_history(study) fig.show()
- Parameters
study (optuna.study.study.Study) – A
Study
object whose trials are plotted for their target values.target (Optional[Callable[[optuna.trial._frozen.FrozenTrial], float]]) –
A function to specify the value to display. If it is
None
andstudy
is being used for single-objective optimization, the objective values are plotted.Note
Specify this argument if
study
is being used for multi-objective optimization.target_name (str) – Target’s name to display on the axis label and the legend.
- Returns
A
plotly.graph_objs.Figure
object.- Raises
ValueError – If
target
isNone
andstudy
is being used for multi-objective optimization.- Return type
plotly.graph_objs._figure.Figure