Title :
Multi-view clustering ensembles
Author :
Xijiong Xie ; Shiliang Sun
Author_Institution :
Dept. of Comput. Sci. & Technol., East China Normal Univ., Shanghai, China
Abstract :
Multi-view clustering and clustering ensembles have become increasingly popular in recent years. Multi-view clustering employs the relationship between views to cluster data; clustering ensembles combine different component clusterings to a better final partition. In this paper, we proposed the multi-view clustering ensembles which extend clustering ensembles to multi-view clustering. Experimental results show good performances of multi-view spectral clustering ensembles and multi-view kernel k-means clustering ensembles on real datasets.
Keywords :
pattern clustering; component clusterings; data clustering; multiview clustering ensembles; multiview kernel k-means clustering ensembles; multiview spectral clustering ensembles; Abstracts; Ionosphere; clustering ensembles; kernel k-means clustering; multi-view clustering; spectral clustering;
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2013 International Conference on
Conference_Location :
Tianjin
DOI :
10.1109/ICMLC.2013.6890443