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: Add condition - require the absolute mean systematic error is less than (max_ratio * RMSE).
  
  Parameters
  ----------
  max_ratio : float , default: 0.01
      Maximum ratio
code: def add_condition_systematic_error_ratio_to_rmse_less_than(
      self, max_ratio: float = 0.01
  ):
      """Add condition - require the absolute mean systematic error is less than (max_ratio * RMSE).
  
      Parameters
      ----------
      max_ratio : float , default: 0.01
          Maximum ratio
      """
  
      def max_bias_condition(result: dict) -> ConditionResult:
          rmse = result["rmse"]
          mean_error = result["mean_error"]
          ratio = abs(mean_error) / rmse
          details = f"Found bias ratio {format_number(ratio)}"
          category = (
              ConditionCategory.PASS
              if ratio < max_ratio
              else ConditionCategory.FAIL
          )
          return ConditionResult(category, details)
  
      return self.add_condition(
          f"Bias ratio is less than {format_number(max_ratio)}",
          max_bias_condition,
      )
  
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 3 for calling the RegressionSystematicError obj's underlying member method code with example usage: obj.add_condition_systematic_error_ratio_to_rmse_less_than(max_ratio) and returns: self, ConditionResult