Comparison of Clustering Algorithm

Authors(2) :-R. Indhu, R. Porkodi

Clustering is a technique used in data mining that groups similar objects into one cluster, while dissimilar objects are grouped into different clusters. Distributed data mining allows for access to volumes of data that are housed at several different company sites or at various organizations. Extremely complicated algorithms are formed to recover the essential data anyway of where it is stored so that it can be useful to a particular data model that will distribute the accurate knowledge and information. The objective of this paper is to perform a comparative analysis of four clustering algorithms namely K-means algorithm, Hierarchical algorithm and Density based algorithm and Expectation maximization algorithm. These algorithms are compared in terms of efficiency and accuracy and observed that K-means produces better results as compared to other algorithms.

Authors and Affiliations

R. Indhu
PG Scholar, Department of Computer Science, Bharathiar University, Coimbator, Tamilnadu, India
R. Porkodi
Assistant Professor, Department of Computer Science, Bharathiar University, Coimbatore, Tamilnadu, India

Clustering, K-means algorithm, Hierarchical algorithm, Expectation and maximization algorithm and Density based algorithm.

  1. https://en.wikipedia.org/wiki/Cluster_analysis
  2. http://googleweblight.com.
  3. Survey of different clustering algorithm in data mining technique in p.Indirapriya Dr.D.K.Ghos2 International Journal of modern engineering research (IJMER).
  4. Clustering in data mining: A Brief Review in Meenu Sharma International Journal of Core Engineering & management (IJCEM)
  5. A Survey of Evolutionary Algorithms for Clustering in Alex A.Freitas,and Andre Capone Leon f. de Carvalho IEEE Transactions on system, man, and Cybernetics part C:Application and review, vol.39.no.2, march 2009.
  6. An analysis on Clustering Algorithm in Data Mining Mythili S1, Madhiya E2 International Journal of Computer Science and mobile Computing.
  7. A Survey on Recent Traffic Classification Techniques Using Machine Learning Methods in M.Tamilkili journal of Advanced Research in Computer Science and Software Engineering.
  8. Survey paper on Clustering Techniques in Amandeep Kaur Mann(M.TECH C.S.E)International journal of Science,Engineering and Technology Research(IJSETR).
  9. Clustering Techniques and the Similarity Measures used in Clustering:A Survey Jasmine lrani Nitinpise Maduraphatak International of Computer Application(0975-8887)Volume 134-No.7,January 2016.
  10. A Survey of Data Mining Clustering Algorithm in Mihika Shah Sindhu Nair International Journal of Computer Applications.
  11. Implementing & Improvisation of K-means Clustering Algorithm in Unnati R. Raval1, ChaitaJani2 International Journal of Computer Science and Mobile Computing.
  12. Survey of Different Data Cluster Algorithm in Sukhvir kaur Sukhvir kaur,International Journal of Computer science and Mobile Computing.
  13. T.T. Nguyen, G. Armitage, A survey of technique or Internet traffic classification using machine learning, IEEE Commun. Surveys Tutor. 10 (4) (2008) 56-76.
  14. J. Erman, A. Mahanti, M. Arlitt, I. Cohen, C. Williamson, Offline/realtime traffic classification using semi-supervised learning, Performance Evaluation 64 (9-12) (2007) 1194-1213.
  15. Jun Zhang, Yang Xiang, Wanlei Zhou, Yu Wang, Unsupervised traffic classification using flow statistical properties and IP packet payload, Journal of Computer and System Sciences 79 (2013) 573-585.
  16. JyotiYadav, Monika Sharma, A Review of K-mean Algorithm, International Journal of Engineering Trends and Technology (IJETT) - Volume 4 Issue 7- July 2013.
  17. G. Sathiya and P. Kavitha, An Efficient Enhanced K-Means Approach with Improved Initial Cluster Centers, Middle-East Journal of Scientific Research 20 (4): 485-491, 2014.

Publication Details

Published in : Volume 3 | Issue 1 | January-February 2018
Date of Publication : 2018-02-28
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 218-223
Manuscript Number : CSEIT183137
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

R. Indhu, R. Porkodi, "Comparison of Clustering Algorithm", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 1, pp.218-223, January-February-2018.
Journal URL : http://ijsrcseit.com/CSEIT183137

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