A new preference classification approach: The λ -dissensus cluster algorithm
José Manuel Cascón Barbero, Teresa González-Arteaga, Rocío de Andrés Calle · Omega · 2022
Preferences and their classification are essential in many decision making processes. However, grouping preferences is not an easy matter because their very nature. In this paper a new preference clustering algorithm is proposed that incorporates the key features of preferences, usually represented by order vectors, and it takes ideas from Social Choice Theory, Decision Making Theory and Cluster Analysis as sources of inspiration. Additionally, a study of the main properties of our proposal is included as well as several internal validation measurements. Finally and in order to improve understanding of the proposed approach, assorted experiments on real data are included.