Fuzzy C-means++: Fuzzy C-means with effective seeding initialization

作者：

Highlights：

• Paper proposes the Fuzzy C-means++ method for improving the effectiveness and speed of the Fuzzy C-means algorithm.

• This method works by spreading the initial cluster representatives in the data space at initialization.

• The proposed algorithm achieves superior results on both artificially generated and real world data sets.

摘要

•Paper proposes the Fuzzy C-means++ method for improving the effectiveness and speed of the Fuzzy C-means algorithm.•This method works by spreading the initial cluster representatives in the data space at initialization.•The proposed algorithm achieves superior results on both artificially generated and real world data sets.

论文关键词：Cluster analysis,Fuzzy C-means clustering,Initialization

论文评审过程：Available online 22 May 2015, Version of Record 19 June 2015.

论文官网地址：https://doi.org/10.1016/j.eswa.2015.05.014