def filter_vectors(self, input_list):
        unique_dict = {}
        for v in input_list:
            unique_dict[v[1]] = v
        return list(unique_dict.values())
Calculate the F1 score of the least frequent label/class in ``y_true`` for
dataset/ETHPy150Open pixelogik/NearPy/nearpy/filters/uniquefilter.py/UniqueFilter.filter_vectors--crossover with--dataset/ETHPy150Open EducationalTestingService/skll/skll/metrics.py/f1_score_least_frequent