docstr: Overview tab of feature importances
  
  Can show both permutation importances and mean absolute shap values.
  
  Args:
      explainer (Explainer): explainer object constructed with either
                  ClassifierExplainer() or RegressionExplainer()
      title (str, optional): Title of tab or page. Defaults to
                  "Feature Importances".
      name (str, optional): unique name to add to Component elements.
                  If None then random uuid is generated to make sure
                  it's unique. Defaults to None.
      hide_title (bool, optional): hide the title
      hide_importances (bool, optional): hide the ImportancesComponent
      hide_descriptions (bool, optional): hide the FeatureDescriptionsComponent
      hide_selector (bool, optional): hide the post label selector.
          Defaults to True.
code: def __init__(
      self,
      explainer,
      title="Feature Importances",
      name=None,
      hide_title=True,
      hide_importances=False,
      hide_descriptions=False,
      hide_selector=True,
      **kwargs,
  ):
      """Overview tab of feature importances
  
      Can show both permutation importances and mean absolute shap values.
  
      Args:
          explainer (Explainer): explainer object constructed with either
                      ClassifierExplainer() or RegressionExplainer()
          title (str, optional): Title of tab or page. Defaults to
                      "Feature Importances".
          name (str, optional): unique name to add to Component elements.
                      If None then random uuid is generated to make sure
                      it's unique. Defaults to None.
          hide_title (bool, optional): hide the title
          hide_importances (bool, optional): hide the ImportancesComponent
          hide_descriptions (bool, optional): hide the FeatureDescriptionsComponent
          hide_selector (bool, optional): hide the post label selector.
              Defaults to True.
      """
      super().__init__(explainer, title, name)
  
      self.importances = ImportancesComponent(
          explainer,
          name=self.name + "0",
          hide_selector=hide_selector,
          **kwargs,
      )
      self.feature_descriptions = FeatureDescriptionsComponent(
          explainer, **kwargs
      )
  
      if not self.explainer.descriptions:
          self.hide_descriptions = True
  
imports: import dash_bootstrap_components
  from dash import html
  from ..explainers import RandomForestExplainer, XGBExplainer
  from ..dashboard_methods import *
  from .classifier_components import *
  from .regression_components import *
  from .overview_components import *
  from .connectors import *
  from .shap_components import *
  from .decisiontree_components import *
  from ..None import to_html
label_desc: Use image node_id 1 to create a new ImportancesComposite object from inherited base classes: ExplainerComponent with example: obj = ImportancesComposite(explainer, title, name, hide_title, hide_importances, hide_descriptions, hide_selector)