Fuzzy C-Means clustering algorithm for data with unequal cluster sizes and contaminated with noise and outliers: Review and development

作者：

Highlights：

• RFCM algorithm removes drawbacks of the FCM algorithm.

• RFCM algorithm eliminates interactions among clusters.

• RFCM algorithm is suitable for data highly contaminated with noise and outliers.

• RFCM algorithm is suitable for data with different cluster densities and sizes.

摘要

•RFCM algorithm removes drawbacks of the FCM algorithm.•RFCM algorithm eliminates interactions among clusters.•RFCM algorithm is suitable for data highly contaminated with noise and outliers.•RFCM algorithm is suitable for data with different cluster densities and sizes.

论文关键词：Fuzzy C-Means,FCM,Clustering,Outlier,Noise,Unequal clusters

论文评审过程：Received 11 March 2020, Revised 13 July 2020, Accepted 6 August 2020, Available online 14 August 2020, Version of Record 27 October 2020.

论文官网地址：https://doi.org/10.1016/j.eswa.2020.113856