def findUncertainPairs(field_distances, classifier, bias=0.5):
    """
    Given a set of field distances and a data model return the
    indices of the record pairs in order of uncertainty. For example,
    the first indices corresponds to the record pair where we have the
    least certainty whether the pair are duplicates or distinct.
    """

    probability = classifier.predict_proba(field_distances)[:,-1]

    p_max = (1 - bias)
    logger.info(p_max)

    informativity = numpy.copy(probability)
    informativity[probability < p_max] /= p_max
    informativity[probability >= p_max] = (1 - probability[probability >= p_max])/(1-p_max)


    return numpy.argmax(informativity)
dataset/ETHPy150Open datamade/dedupe/dedupe/training.py/findUncertainPairs/original