optuna.visualization.plot_parallel_coordinate

optuna.visualization.plot_parallel_coordinate(study, params=None, *, target=None, target_name='Objective Value')[source]

Plot the high-dimentional parameter relationships in a study.

Note that, If a parameter contains missing values, a trial with missing values is not plotted.

Example

The following code snippet shows how to plot the high-dimentional parameter relationships.

import optuna


def objective(trial):
    x = trial.suggest_uniform("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)

optuna.visualization.plot_parallel_coordinate(study, params=["x", "y"])
Parameters
  • study (optuna.study.Study) – A Study object whose trials are plotted for their target values.

  • params (Optional[List[str]]) – Parameter list to visualize. The default is all parameters.

  • target (Optional[Callable[[optuna.trial._frozen.FrozenTrial], float]]) –

    A function to specify the value to display. If it is None and study 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 is None and study is being used for multi-objective optimization.

Return type

plotly.graph_objs._figure.Figure