Subspace clustering with automatic feature grouping

作者：

Highlights：

• We study the problem of subspace clustering with feature grouping.

• We propose a k-means-type algorithm by incorporating feature grouping into the objective function.

• The algorithm is able to determine feature groups automatically.

• Experiments on synthetic and real data show that the algorithm performs well.

摘要

Highlights•We study the problem of subspace clustering with feature grouping.•We propose a k-means-type algorithm by incorporating feature grouping into the objective function.•The algorithm is able to determine feature groups automatically.•Experiments on synthetic and real data show that the algorithm performs well.

论文关键词：Data clustering,Subspace clustering,k-means,Feature group

论文评审过程：Received 30 December 2014, Revised 12 April 2015, Accepted 16 May 2015, Available online 29 May 2015, Version of Record 16 July 2015.

论文官网地址：https://doi.org/10.1016/j.patcog.2015.05.016