Weighted consensus clustering and its application to Big data
作者：
Highlights：
• The paper proposes a purity-based weighted consensus clustering.
• The proposed approach demonstrates the efficient integration of clustering methods.
• The best result shows the proposed approach with the squared Euclidean metric.
• The proposed approach compensates for the shortcomings of each considered method.
• Weighted consensus will allow experts to use it when making group decisions.
摘要
•The paper proposes a purity-based weighted consensus clustering.•The proposed approach demonstrates the efficient integration of clustering methods.•The best result shows the proposed approach with the squared Euclidean metric.•The proposed approach compensates for the shortcomings of each considered method.•Weighted consensus will allow experts to use it when making group decisions.
论文关键词：Weighted consensus clustering,Big data,Utility function,Purity-based utility function,Co-association matrix
论文评审过程：Received 28 November 2018, Revised 9 August 2019, Accepted 5 February 2020, Available online 14 February 2020, Version of Record 21 February 2020.
论文官网地址：https://doi.org/10.1016/j.eswa.2020.113294
