The week's pick
Random Articles
Reseach Article
Comparative Analysis of Clustering Methods
by
Abhineet Saxena,
Lalit Mohan Goyal,
Mamta Mittal
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 118 - Number 21 |
| Year of Publication: 2015 |
| Authors: Abhineet Saxena, Lalit Mohan Goyal, Mamta Mittal |
10.5120/20873-3452
|
Abhineet Saxena, Lalit Mohan Goyal, Mamta Mittal . Comparative Analysis of Clustering Methods. International Journal of Computer Applications. 118, 21 ( May 2015), 30-35. DOI=10.5120/20873-3452
@article{
10.5120/20873-3452,
author = {
Abhineet Saxena,
Lalit Mohan Goyal,
Mamta Mittal
},
title = { Comparative Analysis of Clustering Methods },
journal = {
International Journal of Computer Applications
},
issue_date = { May 2015 },
volume = { 118 },
number = { 21 },
month = { May },
year = { 2015 },
issn = { 0975-8887 },
pages = {
30-35
},
numpages = {9},
url = {
https://ijcaonline.org/archives/volume118/number21/20873-3452/
},
doi = { 10.5120/20873-3452 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:02:23.602561+05:30
%A Abhineet Saxena
%A Lalit Mohan Goyal
%A Mamta Mittal
%T Comparative Analysis of Clustering Methods
%J International Journal of Computer Applications
%@ 0975-8887
%V 118
%N 21
%P 30-35
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract
The innumerable clustering methods which exist today form the basis of Data Mining and Cluster Analysis. This paper details the distinct classifications of clustering methods, describes prominent examples for each such classification and aims to bring about the comparison between the primary clustering techniques which form the basis of all the others, i. e. the Hierarchical and Partitional algorithms.
References
- Agrawal, R. , Gehrke, J. , Gunopulos, D. , & Raghavan, P. (1998). Automatic subspace clustering of high dimensional data for data mining applications (Vol. 27, No. 2, pp. 94-105). ACM.
- Ankerst, M. , Breunig, M. M. , Kriegel, H. P. , & Sander, J. (1999, June). OPTICS: ordering points to identify the clustering structure. In ACM Sigmod Record (Vol. 28, No. 2, pp. 49-60). ACM.
- Arthur, D. , & Vassilvitskii, S. (2007, January). k-means++: The advantages of careful seeding. In Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms (pp. 1027-1035). Society for Industrial and Applied Mathematics.
- Bezdek, J. C. , Ehrlich, R. , & Full, W. (1984). FCM: The fuzzy c-means clustering algorithm. Computers & Geosciences, 10(2), 191-203.
- David Eppstein, Fast Hierarchical Clustering via Dynamic Closest Pairs, Dept. Information and Computer Science, Univ. of California, Irvine, http://www. ics. uci. edu/~eppstein/
- Dempster, A. P. ; Laird, N. M. ; Rubin, D. B. (1977). "Maximum Likelihood from Incomplete Data via the EM Algorithm". Journal of the Royal Statistical Society. Series B (Methodological).
- Ghwanmeh, Sameh H. "Applying Clustering of hierarchical K-means-like Algorithm on Arabic Language. " International Journal of Information Technology3. 3 (2005).
- Gionis, A. , H. Mannila, and P. Tsaparas, Clustering aggregation. ACM Transactions on Knowledge Discovery from Data (TKDD), 2007. 1(1): p. 1-30.
- Jain, A. K. (2010). Data clustering: 50 years beyond K-means. Pattern recognition letters, 31(8), 651-666.
- Kaufman, L. and Rousseeuw, P. J. (1990). Finding Groups in Data: An Introduction to Cluster Analysis. Wiley, New York
- MacQueen, J. B. (1967). Some methods for classification and analysis of multivariate observations. Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability. Berkeley, University of California Press, 1, 281-297.
- Martin Ester and Hans-peter Kriegel and Jörg S and Xiaowei Xu (1996). A density-based algorithm for discovering clusters in large spatial databases with noise. KDD96 Proceedings, AAAI Press, 226-231.
- Mittal, Mamta. "Validation of k-means and Threshold based Clustering Method. " International Journal of Advancements in Technology 5. 2 (2014): 153-160.
- Mittal, M. ; Singh, V. P. ; Sharma, R. K. , "Random automatic detection of clusters," Image Information Processing (ICIIP), 2011 International Conference on Intelligent Information Processing, vol. , no. , pp. 1,6, 3-5 Nov. 2011, doi: 10. 1109/ICIIP. 2011. 6108856.
- Park, Hae-Sang, and Chi-Hyuck Jun. "A simple and fast algorithm for K-medoids clustering. " Expert Systems with Applications 36. 2 (2009): 3336-3341.
- Reddy, Damodar, Prasanta K. Jana, and IEEE Senior Member. "Initialization for K-means clustering using Voronoi diagram. " Procedia Technology 4 (2012): 395-400.
- Wang, W. , Yang, J. , & Muntz, R. (1997, August). STING: A statistical information grid approach to spatial data mining. In VLDB (Vol. 97, pp. 186-195).
- http://cs. joensuu. fi/sipu/datasets/ Speech and Image Processing Unit, School of Computing, University of Eastern Finland, Joensuu, Finland.
Index Terms
Computer Science
Information Sciences
Keywords