# optuna.multi_objective.visualization.plot_pareto_front¶

optuna.multi_objective.visualization.plot_pareto_front(study: optuna.multi_objective.study.MultiObjectiveStudy, names: Optional[List[str]] = None, include_dominated_trials: bool = False) → go.Figure[source]

Plot the pareto front of a study.

Example

The following code snippet shows how to plot the pareto front of a study.

import optuna

def objective(trial):
x = trial.suggest_float("x", 0, 5)
y = trial.suggest_float("y", 0, 3)

v0 = 4 * x ** 2 + 4 * y ** 2
v1 = (x - 5) ** 2 + (y - 5) ** 2
return v0, v1

study = optuna.multi_objective.create_study(["minimize", "minimize"])
study.optimize(objective, n_trials=50)

optuna.multi_objective.visualization.plot_pareto_front(study)

Parameters
• study – A MultiObjectiveStudy object whose trials are plotted for their objective values.

• names – Objective name list used as the axis titles. If None is specified, “Objective {objective_index}” is used instead.

• include_dominated_trials – A flag to include all dominated trial’s objective values.

Returns

A plotly.graph_objs.Figure object.

Raises

ValueError – If the number of objectives of study isn’t 2 or 3.

Note

Added in v2.0.0 as an experimental feature. The interface may change in newer versions without prior notice. See https://github.com/optuna/optuna/releases/tag/v2.0.0.