Multi-view clustering ensembles

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.

[1]  Anil K. Jain,et al.  A Mixture Model for Clustering Ensembles , 2004, SDM.

[2]  Ana L. N. Fred,et al.  Finding Consistent Clusters in Data Partitions , 2001, Multiple Classifier Systems.

[3]  Joydeep Ghosh,et al.  Cluster Ensembles --- A Knowledge Reuse Framework for Combining Multiple Partitions , 2002, J. Mach. Learn. Res..

[4]  Steffen Bickel,et al.  Multi-view clustering , 2004, Fourth IEEE International Conference on Data Mining (ICDM'04).

[5]  Hal Daumé,et al.  Co-regularized Multi-view Spectral Clustering , 2011, NIPS.

[6]  Shiliang Sun,et al.  A survey of multi-view machine learning , 2013, Neural Computing and Applications.

[7]  Xiaoli Z. Fern,et al.  Cluster Ensemble Selection , 2008, Statistical analysis and data mining.

[8]  Aristidis Likas,et al.  Convex Mixture Models for Multi-view Clustering , 2009, ICANN.

[9]  Licheng Jiao,et al.  Bagging-based spectral clustering ensemble selection , 2011, Pattern Recognit. Lett..

[10]  V. D. Sa.  Spectral Clustering with Two Views , 2007 .

[11]  Anil K. Jain,et al.  Clustering ensembles: models of consensus and weak partitions , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[12]  Aristidis Likas,et al.  Kernel-Based Weighted Multi-view Clustering , 2012, 2012 IEEE 12th International Conference on Data Mining.

[13]  Michael I. Jordan,et al.  On Spectral Clustering: Analysis and an algorithm , 2001, NIPS.

[14]  Hal Daumé,et al.  A Co-training Approach for Multi-view Spectral Clustering , 2011, ICML.

[15]  Wei Tang,et al.  Clusterer ensemble , 2006, Knowl. Based Syst..

[16]  Yi Hong,et al.  Resampling-based selective clustering ensembles , 2009, Pattern Recognit. Lett..