docstr: Shows a summary for a particular prediction
  
  Args:
      explainer (Explainer): explainer object constructed with either
                  ClassifierExplainer() or RegressionExplainer()
      title (str, optional): Title of tab or page. Defaults to
                  "Prediction".
      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_index (bool, optional): hide index selector. Defaults to False.
      hide_title (bool, optional): hide title. Defaults to False.
      hide_subtitle (bool, optional): Hide subtitle. Defaults to False.
      hide_table (bool, optional): hide the results table
      index_dropdown (bool, optional): Use dropdown for index input instead
          of free text input. Defaults to True.
      feature_input_component (FeatureInputComponent): A FeatureInputComponent
          that will give the input to the graph instead of the index selector.
          If not None, hide_index=True. Defaults to None.
      index ({int, str}, optional): Index to display prediction summary for. Defaults to None.
      description (str, optional): Tooltip to display when hover over
          component title. When None default text is shown.
code: def __init__(
      self,
      explainer,
      title="Prediction",
      name=None,
      hide_index=False,
      hide_title=False,
      hide_subtitle=False,
      hide_table=False,
      index_dropdown=True,
      feature_input_component=None,
      index=None,
      round=3,
      description=None,
      **kwargs,
  ):
      """Shows a summary for a particular prediction
  
      Args:
          explainer (Explainer): explainer object constructed with either
                      ClassifierExplainer() or RegressionExplainer()
          title (str, optional): Title of tab or page. Defaults to
                      "Prediction".
          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_index (bool, optional): hide index selector. Defaults to False.
          hide_title (bool, optional): hide title. Defaults to False.
          hide_subtitle (bool, optional): Hide subtitle. Defaults to False.
          hide_table (bool, optional): hide the results table
          index_dropdown (bool, optional): Use dropdown for index input instead
              of free text input. Defaults to True.
          feature_input_component (FeatureInputComponent): A FeatureInputComponent
              that will give the input to the graph instead of the index selector.
              If not None, hide_index=True. Defaults to None.
          index ({int, str}, optional): Index to display prediction summary for. Defaults to None.
          description (str, optional): Tooltip to display when hover over
              component title. When None default text is shown.
      """
      super().__init__(explainer, title, name)
  
      self.index_name = "reg-prediction-index-" + self.name
      self.index_selector = IndexSelector(
          explainer,
          self.index_name,
          index=index,
          index_dropdown=index_dropdown,
      )
  
      if self.feature_input_component is not None:
          self.exclude_callbacks(self.feature_input_component)
          self.hide_index = True
  
      if self.description is None:
          self.description = f"""
          Shows the predicted {self.explainer.target} and the observed {self.explainer.target},
          as well as the difference between the two (residual)
          """
  
imports: import numpy
  import pandas
  import dash
  from dash import html, dcc, Input, Output, State
  from dash.exceptions import PreventUpdate
  import dash_bootstrap_components
  from ..dashboard_methods import *
  from ..None import to_html
label_desc: Use image node_id 1 to create a new RegressionPredictionSummaryComponent object from inherited base classes: ExplainerComponent with example: obj = RegressionPredictionSummaryComponent(explainer, title, name, hide_index, hide_title, hide_subtitle, hide_table, index_dropdown, feature_input_component, index, round, description)