class_docstr: This class allows you to define metric thresholds for model validation.
  Allowed thresholds are: threshold, min_absolute_change, min_relative_change.
  
  :param threshold: (Optional) A number representing the value threshold for the metric.
  
                    - If higher is better for the metric, the metric value has to be
                      >= threshold to pass validation.
                    - Otherwise, the metric value has to be <= threshold to pass the validation.
  
  :param min_absolute_change: (Optional) A positive number representing the minimum absolute
                              change required for candidate model to pass validation with
                              the baseline model.
  
                              - If higher is better for the metric, metric value has to be
                                >= baseline model metric value + min_absolute_change
                                to pass the validation.
                              - Otherwise, metric value has to be
                                <= baseline model metric value - min_absolute_change
                                to pass the validation.
  
  :param min_relative_change: (Optional) A floating point number between 0 and 1 representing
                              the minimum relative change (in percentage of
                              baseline model metric value) for candidate model
                              to pass the comparison with the baseline model.
  
                              - If higher is better for the metric, metric value has to be
                                >= baseline model metric value * (1 + min_relative_change)
                              - Otherwise, metric value has to be
                                <= baseline model metric value * (1 - min_relative_change)
                              - Note that if the baseline model metric value is equal to 0, the
                                threshold falls back performing a simple verification that the
                                candidate metric value is better than the baseline metric value,
                                i.e. metric value >= baseline model metric value + 1e-10 if higher
                                is better; metric value <= baseline model metric value - 1e-10 if
                                lower is better.
  
  :param greater_is_better: A required boolean representing whether higher value is
                            better for the metric.
  
  :param higher_is_better:
      .. deprecated:: 2.3.0
          Use ``greater_is_better`` instead.
  
      A required boolean representing whether higher value is better for the metric.
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docstr: Value of the minimum absolute change required to pass model comparison with baseline model.
docstr_tok: ["Value","of","the","minimum","absolute","change","required","to","pass","model","comparison","with","baseline","model","."]
code: def min_absolute_change(self):
      """
      Value of the minimum absolute change required to pass model comparison with baseline model.
      """
      return self._min_absolute_change
  
imports: from mlflow.exceptions import MlflowException
  from mlflow.protos.databricks_pb2 import BAD_REQUEST, INVALID_PARAMETER_VALUE
  from mlflow.utils.annotations import deprecated
label_desc: Use image node_id 3 for calling the MetricThreshold obj's underlying member method code with example usage: obj.min_absolute_change() and returns: self