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

Authors(2) :-B Kalai Selvi, M Ashwin

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.

Authors and Affiliations

B Kalai Selvi
Department of Computer Science and Engineering, Adhiyamaan College of Engineering, Hosur, Tamil Nadu, India
M Ashwin
Department of Computer Science and Engineering, Adhiyamaan College of Engineering, Hosur, Tamil Nadu, India

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

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Publication Details

Published in : Volume 2 | Issue 1 | January-February 2016
Date of Publication : 2016-02-29
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 469-473
Manuscript Number : IJSRSET1621119
Publisher : Technoscience Academy

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

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-February-2016.
Journal URL : http://ijsrset.com/IJSRSET1621119

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