docstr: Composite for a number of component that deal with individual predictions:
  
  - random index selector
  - prediction summary
  - shap contributions graph
  - shap contribution table
  - pdp graph
  
  Args:
      explainer (Explainer): explainer object constructed with either
                  ClassifierExplainer() or RegressionExplainer()
      title (str, optional): Title of tab or page. Defaults to
                  "Individual Predictions".
      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_predindexselector (bool, optional): hide ClassifierRandomIndexComponent
          or RegressionRandomIndexComponent
      hide_predictionsummary (bool, optional): hide ClassifierPredictionSummaryComponent
          or RegressionPredictionSummaryComponent
      hide_contributiongraph (bool, optional): hide ShapContributionsGraphComponent
      hide_pdp (bool, optional): hide PdpComponent
      hide_contributiontable (bool, optional): hide ShapContributionsTableComponent
      hide_title (bool, optional): hide title. Defaults to False.
      index_check (bool, optional): only pass valid indexes from random index
          selector to feature input. Defaults to True.
      hide_selector(bool, optional): hide all pos label selectors. Defaults to True.
code: def __init__(
      self,
      explainer,
      title="Individual Predictions",
      name=None,
      hide_predindexselector=False,
      hide_predictionsummary=False,
      hide_contributiongraph=False,
      hide_pdp=False,
      hide_contributiontable=False,
      hide_title=False,
      hide_selector=True,
      index_check=True,
      **kwargs,
  ):
      """Composite for a number of component that deal with individual predictions:
  
      - random index selector
      - prediction summary
      - shap contributions graph
      - shap contribution table
      - pdp graph
  
      Args:
          explainer (Explainer): explainer object constructed with either
                      ClassifierExplainer() or RegressionExplainer()
          title (str, optional): Title of tab or page. Defaults to
                      "Individual Predictions".
          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_predindexselector (bool, optional): hide ClassifierRandomIndexComponent
              or RegressionRandomIndexComponent
          hide_predictionsummary (bool, optional): hide ClassifierPredictionSummaryComponent
              or RegressionPredictionSummaryComponent
          hide_contributiongraph (bool, optional): hide ShapContributionsGraphComponent
          hide_pdp (bool, optional): hide PdpComponent
          hide_contributiontable (bool, optional): hide ShapContributionsTableComponent
          hide_title (bool, optional): hide title. Defaults to False.
          index_check (bool, optional): only pass valid indexes from random index
              selector to feature input. Defaults to True.
          hide_selector(bool, optional): hide all pos label selectors. Defaults to True.
      """
      super().__init__(explainer, title, name)
  
      if self.explainer.is_classifier:
          self.index = ClassifierRandomIndexComponent(
              explainer, hide_selector=hide_selector, **kwargs
          )
          self.summary = ClassifierPredictionSummaryComponent(
              explainer, hide_selector=hide_selector, **kwargs
          )
      elif self.explainer.is_regression:
          self.index = RegressionRandomIndexComponent(
              explainer, hide_selector=hide_selector, **kwargs
          )
          self.summary = RegressionPredictionSummaryComponent(
              explainer, hide_selector=hide_selector, **kwargs
          )
  
      self.contributions = ShapContributionsGraphComponent(
          explainer, hide_selector=hide_selector, **kwargs
      )
      self.pdp = PdpComponent(
          explainer,
          name=self.name + "3",
          hide_selector=hide_selector,
          **kwargs,
      )
      self.contributions_list = ShapContributionsTableComponent(
          explainer, hide_selector=hide_selector, **kwargs
      )
  
      self.index_connector = IndexConnector(
          self.index,
          [
              self.summary,
              self.contributions,
              self.pdp,
              self.contributions_list,
          ],
          explainer=explainer if index_check else None,
      )
  
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 IndividualPredictionsComposite object from inherited base classes: ExplainerComponent with example: obj = IndividualPredictionsComposite(explainer, title, name, hide_predindexselector, hide_predictionsummary, hide_contributiongraph, hide_pdp, hide_contributiontable, hide_title, hide_selector, index_check)