Clustering ensembles based on multi-classifier fusion

Huang, Yu; Monekosso, Dorothy; Wang, Hui

Abstract

Clustering ensembles can combine multiple partitions generated by different clustering methods into a final superior clustering result. Compared to single clustering algorithm, it can provide better solutions in terms of robustness, novelty and stability. In this paper, we proposed a new method named CEMF, i.e., Clustering Ensembles Based on Multi-classifier Fusion. We combine the clustering ensembles method and multi-classifier method to deal with the clustering consensus problem. CEMF generates multiple partitions and create subspaces which can be used to constructs the local optimum classifiers. CEMF makes use of the advantage of multi-classifiers to assist clustering ensembles in different subs paces of data set. Experiments carried out on some public data sets show that CEMF is comparable or better than classical clustering algorithms and traditional clustering ensembles methods. It's an effective and feasible method. ©2010 IEEE.

• Presentation Conference Type: Conference Paper (Published)
• Conference Name: Proceedings - 2010 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2010
• Start Date: Oct 29, 2010
• End Date: Oct 29, 2010
• Publication Date: Dec 1, 2010
• Journal: Intelligent Computing and Intelligent Systems (ICIS), 2010 IEEE International Conference on
• Peer Reviewed: Not Peer Reviewed
• Volume: 3
• Pages: 393-397
• ISBN: 978-1-4244-6582-8
• DOI: https://doi.org/10.1109/ICICISYS.2010.5658608
• Keywords: breast, cancer, educational institutions, iris recognition, nickel, pattern recognition,; pattern classification, pattern clustering, statistical analysis, unsupervised learning, clustering ensembles, consensus function, multiclassifier fusion, classifica
• Public URL: https://uwe-repository.worktribe.com/output/974155
• Publisher URL: http://dx.doi.org/10.1109/ICICISYS.2010.5658608
• Additional Information: Title of Conference or Conference Proceedings : IEEE International Conference on Intelligent Computing and Intelligent Systems (ICIS 2010)