AN EFFICIENT DENSITY BASED K-MEDOIDS CLUSTERING ALGORITHM

Authors

  • Swarndeep Saket Parul Institute Of Engineering And Technology, Dept. Of Computer Science And Engineering, Vadodara, India.

Keywords:

clustering, k-means, k-medoids

Abstract

The present paper discusses nature and types of clustering techniques and moves on to highlight an efficient density based K Medoids clustering alogrithm. In this study we have proposed a modified K Medoids alogrithm for improving efficiency and scalability for large datasets as a solution.  The paper seeks to enhance accuracy and generate better clusters in large data sets.

References

Banfield J. D. and Raftery A. E.,” Model-based Gaussian and non-Gaussian clustering”, Biometrics, 49:803-821, 1993.

Shalini S singh, N C Chauhan “K-means v/s K-medoids: A Comparative Study”, National Conference on Recent Trends in Engineering & Technology, May 2011.

YujieZheng,"Clustering Methods in Data Mining with its Applications in High Education”, International Conference on Education Technology and Computer, 2012.

Er. Arpit Gupta, Er.Ankit Gupta, Er. Amit Mishra,” RESEARCH PAPER ON CLUSTER TECHNIQUES OF DATA VARIATIONS”, International Journal of Advance Technology & Engineering Research, November 2011, Vol. 1, Issue 1, pp 39-47.

A. Jain, R. Duin, and J. Mao, “Statistical pattern recognition: A review,” IEEE Trans. Pattern Anal. Mach. Intell., 2000, vol. 22, no. 1, pp. 4–37

Bishop, “Neural Networks for Pattern Recognition.”,1995.

C. Chen, L. Pau, and P. Wang, Eds.,”Handbook of Pattern Recognition and Computer Vision”, 1993, pp. 61–124.

J. Kleinberg, “An impossibility theorem for clustering,” in Proc. 2002 Conf. Advances in Neural Information Processing Systems, vol. 15, 2002, pp. 463–470.

C. Chen, L. Pau, and P.Wang, Eds.,“Handbook of Pattern Recognition and Computer Vision” 1993, pp. 3–32.

A. Gordon, C. Hayashi, N. Ohsumi, K. Yajima, Y. Tanaka, H. Bock, and Y. Bada, Eds “Cluster validation,” in Data Science, Classification, and Related Methods. New York: Springer-Verlag, 1998, pp. 22–39.

R. Davé and R. Krishnapuram, “Robust clustering methods: A unified view,” IEEE Trans. Fuzzy Syst., May 1997, vol. 5, no. 2, pp. 270–293.

PrabhdipKaur, ShrutiAggrwal ,” Comparative Study of Clustering Techniques”, international journal for advance research in engineering and technology,April 2013.

S.Anitha Elavarasi and Dr. J. Akilandeswari and Dr. B. Sathiyabhama, January 2011, A Survey On Partition Clustering Algorithms.

Jiawei Han, Micheline Kamber, “Data Mining Concepts and Techniques” Elsevier Publication.

P. Berkhin, 2002. Survey of Clustering Data Mining Techniques. Ttechnical report, AccrueSoftware, San Jose, Cail.

P. Berkhin, 2002. Survey of Clustering Data Mining Techniques. Ttechnical report, AccrueSoftware, San Jose, Cailf..

Banfield J. D. and Raftery A. E.,” Model-based Gaussian and non-Gaussian clustering”, Biometrics, 49:803-821, 1993.

Jiawei Han, Micheline Kamber, “Data Mining Concepts and Techniques” Elsevier Publication.

A. Jain, R. Duin, and J. Mao, “Statistical pattern recognition: A review,” IEEE Trans. Pattern Anal. Mach. Intell., 2000, vol. 22, no. 1, pp. 4–37.

Raghuvira Pratap, K Suvarna Vani, J Rama Devi, Dr.K Nageswara Rao “An Efficient Density Based Improved K-Medoids Clustering Algorithm”, International Journal of Advanced Computer Science and Applications,2011, Vol No:2

Downloads

Published

2016-02-29

Issue

Vol. 5 No. 3 (2016): FEBRUARY 2016

Section

Articles

License

Copyright Notice

Submission of an article implies that the work described has not been published previously (except in the form of an abstract or as part of a published lecture or academic thesis), that it is not under consideration for publication elsewhere, that its publication is approved by all authors and tacitly or explicitly by the responsible authorities where the work was carried out, and that, if accepted, will not be published elsewhere in the same form, in English or in any other language, without the written consent of the Publisher. The Editors reserve the right to edit or otherwise alter all contributions, but authors will receive proofs for approval before publication.

Copyrights for articles published in World Scholars journals are retained by the authors, with first publication rights granted to the journal. The journal/publisher is not responsible for subsequent uses of the work. It is the author's responsibility to bring an infringement action if so desired by the author.