Distance metric learning for soft subspace clustering in composite kernel space
作者：
Highlights：
• The composite kernel space is constructed based on a set of basis kernels.
• The general form of soft subspace clustering in CKS is presented.
• CKS-EWFC-K and CKS-EWFC-F are proposed under the framework of CKS-SSC.
• The properties of CKS-EWFC-K and CKS-EWFC-F are investigated.
• Both CKS-EWFC-K and CKS-EWFC-F are immune to ineffective kernels.
摘要
•The composite kernel space is constructed based on a set of basis kernels.•The general form of soft subspace clustering in CKS is presented.•CKS-EWFC-K and CKS-EWFC-F are proposed under the framework of CKS-SSC.•The properties of CKS-EWFC-K and CKS-EWFC-F are investigated.•Both CKS-EWFC-K and CKS-EWFC-F are immune to ineffective kernels.
论文关键词：Fuzzy clustering,Soft subspace clustering,Composite kernel space,Distance metric learning
论文评审过程：Received 11 November 2014, Revised 30 September 2015, Accepted 26 October 2015, Available online 9 November 2015, Version of Record 24 December 2015.
论文官网地址：https://doi.org/10.1016/j.patcog.2015.10.018
