Automatic multi-objective clustering based on game theory
作者：
Highlights：
• Novel multi-objective clustering algorithm based-sequential games was proposed.
• It optimizes simultaneously and efficiently multiple conflicting objectives.
• Proposed approach can automatically calculate the optimal number of clusters.
• This algorithm shows good performance of generating high-quality solutions.
• Experimental study demonstrates the effectiveness of our algorithm over others.
摘要
•Novel multi-objective clustering algorithm based-sequential games was proposed.•It optimizes simultaneously and efficiently multiple conflicting objectives.•Proposed approach can automatically calculate the optimal number of clusters.•This algorithm shows good performance of generating high-quality solutions.•Experimental study demonstrates the effectiveness of our algorithm over others.
论文关键词：Multi-objective clustering,Sequential game,Backward induction,Nash equilibrium
论文评审过程：Received 18 January 2016, Revised 1 September 2016, Accepted 5 September 2016, Available online 20 September 2016, Version of Record 24 September 2016.
论文官网地址：https://doi.org/10.1016/j.eswa.2016.09.008
