A family of distances for preference–approvals
提出一种新的距离度量方法，用于衡量偏好-认可数据间的差异，同时考虑偏好顺序和认可分歧，并在聚类问题中证明其比现有方法更稳定、更准确。
Abstract A preference–approval on a set of alternatives consists of a weak order on that set and, additionally, a cut-off line that separates acceptable and unacceptable alternatives. In this paper, we propose a new method for defining the distance between preference–approvals taking into account jointly the disagreements in preferences and approvals for each pair of alternatives. The proposed distance is compared to the existing distance functions to deal with clustering problems. Specifically, we prove that our metric improves the estimated clusters in terms of both stability and accuracy.