(precision, recall, beta2)
return _non_nan(
      (beta2 + 1) * (precision * recall) / ((beta2 * precision) + recall))
Returns F-score.

  Args:
    precision: a precision score.
    recall: a recall score.
    beta2: a square of the parameter that determines the weight of recall.

  A support function to calculate F-score for the single category.
Returns F-score.
Returns F - score .
def _f_score(precision, recall, beta2):  # pylint: disable=invalid-name
  """Returns F-score.

  Args:
    precision: a precision score.
    recall: a recall score.
    beta2: a square of the parameter that determines the weight of recall.

  A support function to calculate F-score for the single category.
  """
  return _non_nan(
      (beta2 + 1) * (precision * recall) / ((beta2 * precision) + recall))
def _f_score ( precision , recall , beta2 ) : # pylint: disable=invalid-name return _non_nan ( ( beta2 + 1 ) * ( precision * recall ) / ( ( beta2 * precision ) + recall ) )