Back to Search Start Over

Multiple Flat Projections for Cross-Manifold Clustering

Authors :
Yuan-Hai Shao
Lan Bai
Nai-Yang Deng
Zhen Wang
Wei-Jie Chen
Source :
IEEE Transactions on Cybernetics. 52:7704-7718
Publication Year :
2022
Publisher :
Institute of Electrical and Electronics Engineers (IEEE), 2022.

Abstract

Cross-manifold clustering is a hard topic and many traditional clustering methods fail because of the cross-manifold structures. In this paper, we propose a Multiple Flat Projections Clustering (MFPC) to deal with cross-manifold clustering problems. In our MFPC, the given samples are projected into multiple subspaces to discover the global structures of the implicit manifolds. Thus, the cross-manifold clusters are distinguished from the various projections. Further, our MFPC is extended to nonlinear manifold clustering via kernel tricks to deal with more complex cross-manifold clustering. A series of non-convex matrix optimization problems in MFPC are solved by a proposed recursive algorithm. The synthetic tests show that our MFPC works on the cross-manifold structures well. Moreover, experimental results on the benchmark datasets show the excellent performance of our MFPC compared with some state-of-the-art clustering methods.<br />Comment: 12 pages, 58 figures

Details

ISSN :
21682275 and 21682267
Volume :
52
Database :
OpenAIRE
Journal :
IEEE Transactions on Cybernetics
Accession number :
edsair.doi.dedup.....dd536ee9d3dd0fce473dd0bba9cb06fd