def METHOD_NAME(
    study: Study,
    evaluator: BaseImportanceEvaluator | None = None,
    params: list[str] | None = None,
    *,
    target: Callable[[FrozenTrial], float] | None = None,
    target_name: str = "Objective Value",
) -> "go.Figure":
    """Plot hyperparameter importances.
    Example:
        The following code snippet shows how to plot hyperparameter importances.
        .. plotly::
            import optuna
            def objective(trial):
                x = trial.suggest_int("x", 0, 2)
                y = trial.suggest_float("y", -1.0, 1.0)
                z = trial.suggest_float("z", 0.0, 1.5)
                return x ** 2 + y ** 3 - z ** 4
            sampler = optuna.samplers.RandomSampler(seed=10)
            study = optuna.create_study(sampler=sampler)
            study.optimize(objective, n_trials=100)
            fig = optuna.visualization.plot_param_importances(study)
            fig.show()
    .. seealso::
        This function visualizes the results of :func:`optuna.importance.get_param_importances`.
    Args:
        study:
            An optimized study.
        evaluator:
            An importance evaluator object that specifies which algorithm to base the importance
            assessment on.
            Defaults to
            :class:`~optuna.importance.FanovaImportanceEvaluator`.
        params:
            A list of names of parameters to assess.
            If :obj:`None`, all parameters that are present in all of the completed trials are
            assessed.
        target:
            A function to specify the value to display. If it is :obj:`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. For example, to get the hyperparameter importance of the first
                objective, use ``target=lambda t: t.values[0]`` for the target parameter.
        target_name:
            Target's name to display on the axis label.
    Returns:
        A :class:`plotly.graph_objs.Figure` object.
    """
    _imports.check()
    importances_info = _get_importances_info(study, evaluator, params, target, target_name)
    hover_template = _get_hover_template(importances_info, study)
    return _get_importances_plot(importances_info, hover_template)