IJSRSET calls volunteers interested to contribute towards the scientific development in the field of Science, Engineering and Technology

Home > IJSRSET1621119                                                     

FCM : Fuzzy C-Means Clustering - A View in Different Aspects


B Kalai Selvi, M Ashwin
  • Abstract
  • Authors
  • Keywords
  • References
  • Details
Data Mining is the process of obtaining or exploring data from the large amount of raw data. It produces the meaningful information. To obtain the information data mining has multiple techniques such as classification, regression, prediction, clustering, and summarization. There are multiple tasks in data mining to obtain the information such as cleaning, integrating, selection, transformation, pattern evaluation. One of the challenging techniques in the data mining is clustering. Clustering is the process of grouping the data under some condition. The main aim of the paper is to describe about the Fuzzy C-Means Clustering (FCM) and compared with K-Means clustering. The pitfalls overcome by the FCM are also measured theoretically.

B Kalai Selvi, M Ashwin

Clustering, Data Mining, FCM, C-means, K-Means, Fuzzy

  1. Jiawei Han, Micheline Kamber and Jian Pei, ”Data Mining Concepts and Techniques”, 3rd ed. Elsevier
  2. Bo Gao and Jun Wang,” Multi-Objective Fuzzy Clustering for Synthetic Aperture Radar Imagery”, IEEE TRANS. ON GEOSCIENCE AND REMOTE SENSING LETTERS .,VOL 12., ISSUE 11.,2015
  3. B.G.Lee., J.H.Park., W.Y.Chung ,” Smartwatch-based Driver Vigilance Indicator with Kernal-Fuzzy-C-Means-Wavelet Method” IEEE TRANSACTION ON SENSORS JOURNAL, VOL 16., ISSUE 1., 2015
  4. Guoying Liu, Yun Zhang, and Aimin Wang,” Incorporating Adaptive Local Information IntoFuzzy Clustering for Image Segmentation “ IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 24, NO. 11, NOVEMBER 2015
  5. Li Liu, Aolei Yang ,Wenju Zhou, Xiaofeng Zhang, Minrui Fei, and Xiaowei Tu,” Robust Dataset Classification Approach Based onNeighbor Searching and Kernel Fuzzy C-Means” IEEE/CAA JOURNAL OF AUTOMATICA SINICA, VOL. 2, NO. 3, JULY 2015
  6. Jonathon K. Parker and Lawrence O. Hall.,” Accelerating Fuzzy-C Means Using an EstimatedSubsample Size”,IEEE TRANSACTIONS ON FUZZY SYSTEMS, VOL. 22, NO. 5, OCTOBER 2014
  7. Pradipta Maji and Sushmita Paul,” Rough-Fuzzy Clustering for GroupingFunctionally Similar Genes fromMicroarray Data”,IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS, VOL. 10, NO. 2, MARCH/APRIL 2013
  8. Nikhil R. Pal, Kuhu Pal, James M. Keller, and James C. Bezdek.” A Possibilistic Fuzzy c-Means Clustering Algorithm”,IEEE TRANSACTIONS ON FUZZY SYSTEMS, VOL. 13, NO. 4, AUGUST 2005
  9. Pradipta Maji and Sankar K. Pal,” Rough Set Based Generalized Fuzzy C-MeansAlgorithm and Quantitative Indices”, IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART B: CYBERNETICS, VOL. 37, NO. 6, DECEMBER 2007
  10. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1 .300.7332&rep=rep1&type=pdf
  11. http://infoman.teikav.edu.gr/~stkrini/pdfFiles/journals/2010 _TIP.pdf
  12. http://www.indjst.org/index.php/indjst/article/viewFile/ 47757/41449
  13. www.ise.bgu.ac.il/faculty/liorr/hbchap15.pdf
  14. Junjie Wu , ” Advances in k-means Clustering A Data Mining Thinking”, Springer Theses Recognizing Outstanding Ph.D. Research.

Publication Details

Published in : Volume 2 | Issue 1 | January-Febuary - 2016
Date of Publication Print ISSN Online ISSN
2016-02-29 2395-1990 2394-4099
Page(s) Manuscript Number   Publisher
469-473 IJSRSET1621119   Technoscience Academy

Cite This Article

B Kalai Selvi, M Ashwin, "FCM : Fuzzy C-Means Clustering - A View in Different Aspects", International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 2, Issue 1, pp.469-473, January-Febuary-2016.
URL : http://ijsrset.com/IJSRSET1621119.php




National Conference on Advances in Mechanical Engineering 2017(NCAME 2017)

National Conference on Emerging Trends in Civil Engineering 2017( NCETCE 2017)