class_docstr: Relative coefficient of discrimination metric.
  
  The relative coefficient of discrimination measures the ratio between the
  average prediction for the positive examples and the average prediction for
  the negative examples. This has a very simple intuitive explanation, measuring
  how much higher is the prediction going to be for a positive example than for
  a negative example.
docstr: Initializes relative coefficient of discrimination metric.
  
  Args:
    name: Metric name.
docstr_tok: ["Initializes","relative","coefficient","of","discrimination","metric",".","Args",":","name",":","Metric","name","."]
code: def __init__(
      self, name: str = RELATIVE_COEFFICIENT_OF_DISCRIMINATION_NAME
  ):
      """Initializes relative coefficient of discrimination metric.
  
      Args:
        name: Metric name.
      """
      super().__init__(
          metric_util.merge_per_key_computations(
              _relative_coefficient_of_discrimination
          ),
          name=name,
      )
  
imports: from typing import Any, Dict, Iterable, Optional
  import apache_beam
  from tensorflow_model_analysis.metrics import metric_types
  from tensorflow_model_analysis.metrics import metric_util
  from tensorflow_model_analysis.proto import config_pb2
label_desc: Use image node_id 1 to create a new RelativeCoefficientOfDiscrimination object from inherited base classes: metric_types with example: obj = RelativeCoefficientOfDiscrimination(name)