class_docstr: Check for systematic error and abnormal shape in the regression error distribution.
  
  The check shows the distribution of the regression error, and enables to set conditions on two
  of the distribution parameters: Systematic error and Kurtosis value.
  Kurtosis is a measure of the shape of the distribution, helping us understand if the distribution
  is significantly "wider" from a normal distribution.
  Systematic error, otherwise known as the error bias, is the mean prediction error of the model.
  
  Parameters
  ----------
  n_top_samples : int , default: 3
      amount of samples to show which have the largest under / over estimation errors.
  n_bins : int , default: 40
      number of bins to use for the histogram.
  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.
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docstr: Add condition - require systematic error (mean error) lower than (max_ratio * RMSE).
  
  Parameters
  ----------
  max_ratio : float , default: 0.01
      Maximum ratio allowed between the mean error and the rmse value
docstr_tok: ["Add","condition","-","require","systematic","error","(","mean","error",")","lower","than","(","max_ratio","*","RMSE",")",".","Parameters","--","--","--","--","--","max_ratio",":","float",",","default",":","0.01","Maximum","ratio","allowed","between","the","mean","error","and","the","rmse","value"]
code: def add_condition_systematic_error_ratio_to_rmse_less_than(
      self, max_ratio: float = 0.01
  ):
      """Add condition - require systematic error (mean error) lower than (max_ratio * RMSE).
  
      Parameters
      ----------
      max_ratio : float , default: 0.01
          Maximum ratio allowed between the mean error and the rmse value
      """
  
      def max_bias_condition(
          result: Dict[str, float]
      ) -> ConditionResult:
          ratio = abs(result["Mean Prediction Error"]) / result["RMSE"]
          details = f"Found systematic error to rmse ratio of {format_number(ratio)}"
          category = (
              ConditionCategory.PASS
              if ratio < max_ratio
              else ConditionCategory.FAIL
          )
          return ConditionResult(category, details)
  
      return self.add_condition(
          f"Systematic error ratio lower than {format_number(max_ratio)}",
          max_bias_condition,
      )
  
file_path: deepchecks/deepchecks/tabular/checks/model_evaluation/regression_error_distribution.py
imports: from typing import Dict
  import numpy
  import pandas
  import plotly.express
  from scipy.stats import kurtosis
  from sklearn.metrics import mean_squared_error
  from deepchecks.core import CheckResult, ConditionCategory, ConditionResult
  from deepchecks.tabular import Context, SingleDatasetCheck
  from deepchecks.utils.strings import format_number
label_desc: Use image node_id 4 for calling the RegressionErrorDistribution 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