class_docstr: Check the regression systematic error.
  
  Parameters
  ----------
  n_samples : int , default: 1_000_000
      number of samples to use for this check.
  random_state : int, default: 42
      random seed for all check internals.
docstr: Run check.
  
  Returns
  -------
  CheckResult
      value is a dict with rmse and mean prediction error.
      display is box plot of the prediction error.
  
  Raises
  ------
  DeepchecksValueError
      If the object is not a Dataset instance with a label.
code: def run_logic(self, context: Context, dataset_kind) -> CheckResult:
      """Run check.
  
      Returns
      -------
      CheckResult
          value is a dict with rmse and mean prediction error.
          display is box plot of the prediction error.
  
      Raises
      ------
      DeepchecksValueError
          If the object is not a Dataset instance with a label.
      """
      dataset = context.get_data_by_kind(dataset_kind).sample(
          self.n_samples, random_state=self.random_state
      )
      context.assert_regression_task()
      y_test = dataset.label_col
      x_test = dataset.features_columns
      y_pred = context.model.predict(x_test)
  
      rmse = mean_squared_error(y_test, y_pred, squared=False)
      diff = y_test - y_pred
      diff_mean = diff.mean()
  
      if context.with_display:
          fig = (
              go.Figure()
              .add_trace(
                  go.Box(
                      x=diff,
                      orientation="h",
                      name="Model prediction error",
                      hoverinfo="x",
                      boxmean=True,
                  )
              )
              .update_layout(
                  title_text="Box plot of the model prediction error",
                  height=500,
              )
          )
  
          display = [
              "Non-zero mean of the error distribution indicated the presents "
              "of systematic error in model predictions",
              fig,
          ]
      else:
          display = None
  
      return CheckResult(
          value={"rmse": rmse, "mean_error": diff_mean}, display=display
      )
  
file_path: deepchecks/deepchecks/tabular/checks/model_evaluation/regression_systematic_error.py
imports: import warnings
  import plotly.graph_objects
  from sklearn.metrics import mean_squared_error
  from deepchecks.core import CheckResult, ConditionResult
  from deepchecks.core.condition import ConditionCategory
  from deepchecks.tabular import Context, SingleDatasetCheck
  from deepchecks.utils.strings import format_number
label_desc: Use image node_id 2 for calling the RegressionSystematicError obj's underlying member method code with example usage: obj.run_logic(context, dataset_kind) and returns: CheckResult