def create_adjusted_predictor(threshold_optimization_method,
sensitive_features, labels, scores):
post_processed_predictor_by_sensitive_feature = threshold_optimization_method(
sensitive_features, labels, scores)
return lambda sensitive_features_, scores: _vectorized_prediction(
post_processed_predictor_by_sensitive_feature, sensitive_features_,
scores)
def prob_pred(sensitive_features, scores):
return _vectorized_prediction(
estimator._post_processed_predictor_by_sensitive_feature,
sensitive_features, scores)