Stratified feature sampling method for ensemble clustering of high dimensional data
作者：
Highlights：
• A new component generation approach is proposed to produce ensemble components.
• Stratified sampling is used to generate subspace component data sets.
• The component data can well represent the characteristics of the original data.
• The proposed method can achieve a consistent performance in ensemble clustering.
• The proposed method is easy to implement.
摘要
Highlights•A new component generation approach is proposed to produce ensemble components.•Stratified sampling is used to generate subspace component data sets.•The component data can well represent the characteristics of the original data.•The proposed method can achieve a consistent performance in ensemble clustering.•The proposed method is easy to implement.
论文关键词：Stratified sampling,Ensemble clustering,High dimensional data,Consensus function
论文评审过程：Received 18 June 2013, Revised 19 August 2014, Accepted 2 May 2015, Available online 13 May 2015, Version of Record 16 July 2015.
论文官网地址：https://doi.org/10.1016/j.patcog.2015.05.006
