A SOM prototype-based cluster analysis methodology

作者：

Highlights：

• An original computational approach for cluster analysis is proposed.

• The method consists of two phases, which are based on Self-Organizing Map.

• Topology-preserving and connectivity functions are used in the clustering process.

• The method is proved using three benchmark datasets and a real biological dataset.

• Automation in parameterization results in a user-friendly methodology.

摘要

•An original computational approach for cluster analysis is proposed.•The method consists of two phases, which are based on Self-Organizing Map.•Topology-preserving and connectivity functions are used in the clustering process.•The method is proved using three benchmark datasets and a real biological dataset.•Automation in parameterization results in a user-friendly methodology.

论文关键词：Self-organizing map,Clustering,Unsupervised,Topology preserving,Metabolic network

论文评审过程：Received 4 February 2017, Revised 8 June 2017, Accepted 14 June 2017, Available online 15 June 2017, Version of Record 3 July 2017.

论文官网地址：https://doi.org/10.1016/j.eswa.2017.06.022