Many-objective fuzzy centroids clustering algorithm for categorical data

作者：

Highlights：

• We propose a novel many-objective clustering algorithm for categorical data.

• Our method can take advantage of different cluster validity indices simultaneously.

• Two versions of the proposed algorithm are presented with and without cluster number.

• The finding can be instructive for solving other real-world optimization problems.

摘要

•We propose a novel many-objective clustering algorithm for categorical data.•Our method can take advantage of different cluster validity indices simultaneously.•Two versions of the proposed algorithm are presented with and without cluster number.•The finding can be instructive for solving other real-world optimization problems.

论文关键词：Categorical data,Clustering,Many-objective optimization,Cluster validity index,Fuzzy centroids

论文评审过程：Received 10 September 2017, Revised 6 December 2017, Accepted 6 December 2017, Available online 7 December 2017, Version of Record 22 December 2017.

论文官网地址：https://doi.org/10.1016/j.eswa.2017.12.013