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

Authors(2):

B Kalai Selvi, M Ashwin
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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

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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.
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