Improved K-Mean Clustering Algorithm in Data Mining

Authors(1) :-Dhawal Gupta

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Authors and Affiliations

Dhawal Gupta
Assistant Professor, Department of Computer Science and Engineering, Jabalpur, Madhya Pradesh, India

Kmean, Centroid, K-mean plus plus, data objects, Optimization, Wcss

  1. M. S. V. K. Pang-NingTan, “Data mining,” in Introduction to data mining, Pearson International Edition , 2018, pp. 2-7.
  2. J. Peng and Y. Wei, “Approximating k-means-type clustering via semi definite programming,” SIAM Journal on Optimization, vol. 18, 2017.
  3. D.Alexander,“DataMining,”Online].Available:http://www.laits.utexas.edu/~norman/BUS.FOR/course.mat/Alex/.
  4. “What is Data Repository,” GeekInterview, 4 June 2016. Online]. Available:http://www.learn.geekinterview.com/data-warehouse/dw-basics/what-is-data-repository.html.
  5. Fayyad, Usama; Gregory Piatetsky-Shapiro, and Padhraic Smyth (2017) ,from Data mining toknowledge discovery in data base
  6. M. S. V. K. Pang-NingTan, “Data mining,” in Introduction to data mining, Pearson International Edition , 2017 pp. 8.
  7. M. S. V. K. Pang-NingTan, “Data mining,” in Introduction to data mining, Pearson International Edition , 2014, pp. 7-11.
  8. Han, Jiawei, Kamber, Micheline. (2014) Data Mining: Concepts and Techniques. Morgan Kaufmann. 
  9. M. S. V. K. Pang-NingTan, “Data mining,” in Introduction to data mining, Pearson International Edition , 2016, pp. 487-496.
  10. “An Introduction to Cluster Analysis for Data Mining,” 2013. Online]. Available: http://www.cs.umn.edu/~han/dmclass/cluster_survey_10_02_00.
  11. Joaquín Pérez Ortega, Ma. Del Rocío Boone Rojas, María J. Somodevilla García Research issues on, K-means Algorithm: An Experimental Trial Using Matlab
  12. J. MacQueen, “Some Methods For Classification And Analysis Of Multivariate Observations,” In proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability, University of California Press, 2015, pp. 281-297

Publication Details

Published in : Volume 6 | Issue 4 | July-August 2019
Date of Publication : 2019-07-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 87-92
Manuscript Number : IJSRSET19643
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

Dhawal Gupta, " Improved K-Mean Clustering Algorithm in Data Mining, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 6, Issue 4, pp.87-92, July-August-2019. Citation Detection and Elimination     |     
Journal URL : https://ijsrset.com/IJSRSET19643

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