def METHOD_NAME(self, doc_ids: List[str], search_scores: List[float]):
    train_vecs, train_labels, test_vecs = self._get_prf_vectors(doc_ids)
    # classification
    self.clf.fit(train_vecs, train_labels)
    pred = self.clf.predict_proba(test_vecs)
    classifier_scores = self._normalize([p[1] for p in pred])
    search_scores = self._normalize(search_scores)
    # interpolation
    interpolated_scores = [a * self.alpha + b * (1-self.alpha) for a, b in zip(classifier_scores, search_scores)]
    return self._sort_dual_list(interpolated_scores, doc_ids)