Combining clustering solutions with varying number of clusters
Cluster ensemble algorithms have been used in different fields like data mining, bioinformatics and pattern recognition. Many of them use label correspondence as a step which can be performed with some accuracy if all the input partitions are generated with same k. Thus these algorithms produce good results if this k is close to the actual number of clusters in the dataset. This puts great restriction if user has no idea of the number of clusters. In this paper we show through experimental studies that good ensembles can be generated even if the input solutions contain different number of clusters.
Keywords: Clustering, Cluster Ensemble
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ABOUT THE AUTHORS
Geeta Aggarwal
Geeta Aggarwal did her graduation in Computer Science from the University of Delhi, India in 1988. She did her masters in Computer Science from Banasthali Vidyapeeth in 1990. She worked as Systems Analyst in National Informatics Centre,Delhi for a short period following which she joined PGDAV College, University of Delhi in 1996. She is an associate professor and presently pursuing Ph.D. under Dr. Neelima Gupta in the field of Bioinformatics.
Saurabh Garg
Saurabh Garg is a computer science graduate from Hansraj College, University of Delhi and is currently pursuing his MCA from the Department of Computer Sc., University of Delhi. His interests are algorithms and programming. He is an active freelance programmer for 4 years and has carried out several projects of his own.
Neelima Gupta
Neelima Gupta} graduated with a B.Sc. in Mathematics from the University of Delhi, India in 1985. She then went on to complete her M.Sc. in Mathematics in 1987 and M.Tech. in Computer Science in 1989 from the Indian Institute of Technology, Delhi (IITD), India. She received her Ph.D. in Computer Science from IITD in 1998, where she worked on designing randomized parallel algorithms for a number of problems in computational geometry. Earlier in her career, after her M.Tech. she briefly held the position of a Software Engineer at HCL Technologies Pvt. Ltd., in New Delhi, India in 1989. She then joined HansRaj college at University of Delhi in 1989. She is presently an associate professor in the Department of Computer Science at University of Delhi, which she joined in the year 2002. Her research interests include approximation algorithms for network design problems, networks, data mining and bioinformatics. She has published a number of papers in conferences and journals of high repute.
Geeta Aggarwal
Geeta Aggarwal did her graduation in Computer Science from the University of Delhi, India in 1988. She did her masters in Computer Science from Banasthali Vidyapeeth in 1990. She worked as Systems Analyst in National Informatics Centre,Delhi for a short period following which she joined PGDAV College, University of Delhi in 1996. She is an associate professor and presently pursuing Ph.D. under Dr. Neelima Gupta in the field of Bioinformatics.
Saurabh Garg
Saurabh Garg is a computer science graduate from Hansraj College, University of Delhi and is currently pursuing his MCA from the Department of Computer Sc., University of Delhi. His interests are algorithms and programming. He is an active freelance programmer for 4 years and has carried out several projects of his own.
Neelima Gupta
Neelima Gupta} graduated with a B.Sc. in Mathematics from the University of Delhi, India in 1985. She then went on to complete her M.Sc. in Mathematics in 1987 and M.Tech. in Computer Science in 1989 from the Indian Institute of Technology, Delhi (IITD), India. She received her Ph.D. in Computer Science from IITD in 1998, where she worked on designing randomized parallel algorithms for a number of problems in computational geometry. Earlier in her career, after her M.Tech. she briefly held the position of a Software Engineer at HCL Technologies Pvt. Ltd., in New Delhi, India in 1989. She then joined HansRaj college at University of Delhi in 1989. She is presently an associate professor in the Department of Computer Science at University of Delhi, which she joined in the year 2002. Her research interests include approximation algorithms for network design problems, networks, data mining and bioinformatics. She has published a number of papers in conferences and journals of high repute.
