docstr: Composite for displaying multiple regression related graphs:
  
  - predictions vs actual plot
  - residual plot
  - residuals vs feature
  
  Args:
      explainer (Explainer): explainer object constructed with either
                  ClassifierExplainer() or RegressionExplainer()
      title (str, optional): Title of tab or page. Defaults to
                  "Regression Stats".
      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 title. Defaults to True.
      hide_modelsummary (bool, optional): hide RegressionModelSummaryComponent
      hide_predsvsactual (bool, optional): hide PredictedVsActualComponent
      hide_residuals (bool, optional): hide ResidualsComponent
      hide_regvscol (bool, optional): hide RegressionVsColComponent
      logs (bool, optional): Use log axis. Defaults to False.
      pred_or_actual (str, optional): plot residuals vs predictions
                  or vs y (actual). Defaults to "vs_pred".
      residuals (str, {'difference', 'ratio', 'log-ratio'} optional):
              How to calcualte residuals. Defaults to 'difference'.
      col ({str, int}, optional): Feature to use for residuals plot. Defaults to None.
code: def __init__(
      self,
      explainer,
      title="Regression Stats",
      name=None,
      hide_title=True,
      hide_modelsummary=False,
      hide_predsvsactual=False,
      hide_residuals=False,
      hide_regvscol=False,
      logs=False,
      pred_or_actual="vs_pred",
      residuals="difference",
      col=None,
      **kwargs,
  ):
      """Composite for displaying multiple regression related graphs:
  
      - predictions vs actual plot
      - residual plot
      - residuals vs feature
  
      Args:
          explainer (Explainer): explainer object constructed with either
                      ClassifierExplainer() or RegressionExplainer()
          title (str, optional): Title of tab or page. Defaults to
                      "Regression Stats".
          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 title. Defaults to True.
          hide_modelsummary (bool, optional): hide RegressionModelSummaryComponent
          hide_predsvsactual (bool, optional): hide PredictedVsActualComponent
          hide_residuals (bool, optional): hide ResidualsComponent
          hide_regvscol (bool, optional): hide RegressionVsColComponent
          logs (bool, optional): Use log axis. Defaults to False.
          pred_or_actual (str, optional): plot residuals vs predictions
                      or vs y (actual). Defaults to "vs_pred".
          residuals (str, {'difference', 'ratio', 'log-ratio'} optional):
                  How to calcualte residuals. Defaults to 'difference'.
          col ({str, int}, optional): Feature to use for residuals plot. Defaults to None.
      """
      super().__init__(explainer, title, name)
  
      assert pred_or_actual in [
          "vs_actual",
          "vs_pred",
      ], "pred_or_actual should be 'vs_actual' or 'vs_pred'!"
  
      self.modelsummary = RegressionModelSummaryComponent(
          explainer, name=self.name + "0", **kwargs
      )
      self.preds_vs_actual = PredictedVsActualComponent(
          explainer, name=self.name + "0", logs=logs, **kwargs
      )
      self.residuals = ResidualsComponent(
          explainer,
          name=self.name + "1",
          pred_or_actual=pred_or_actual,
          residuals=residuals,
          **kwargs,
      )
      self.reg_vs_col = RegressionVsColComponent(
          explainer, name=self.name + "2", logs=logs, **kwargs
      )
  
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 RegressionModelStatsComposite object from inherited base classes: ExplainerComponent with example: obj = RegressionModelStatsComposite(explainer, title, name, hide_title, hide_modelsummary, hide_predsvsactual, hide_residuals, hide_regvscol, logs, pred_or_actual, residuals, col)