Evaluation and selection of clustering methods using a hybrid group MCDM

作者：

Highlights：

• Clustering comparison with regard to external and internal evaluation indicators.

• Proposing group MCDM framework in order to evaluate the clustering algorithms.

• Presenting a robust clustering ranking via Borda for aggregating MCDM algorithms.

• Introducing a new hybrid PSO-clustering approach.

摘要

•Clustering comparison with regard to external and internal evaluation indicators.•Proposing group MCDM framework in order to evaluate the clustering algorithms.•Presenting a robust clustering ranking via Borda for aggregating MCDM algorithms.•Introducing a new hybrid PSO-clustering approach.

论文关键词：Clustering,MCDM,Group TOPSIS,Group COPRAS,Particle Swarm Optimization

论文评审过程：Received 29 April 2019, Revised 14 July 2019, Accepted 14 July 2019, Available online 15 July 2019, Version of Record 20 July 2019.

论文官网地址：https://doi.org/10.1016/j.eswa.2019.07.034