DocumentCode :
3585851
Title :
Comparison of major clustering algorithms using Weka tool
Author :
Gunasekara, R.P.T.H. ; Wijegunasekara, M.C. ; Dias, N.G.J.
Author_Institution :
Dept. of Comput. & Inf. Syst., Wayamba Univ. of Sri Lanka, Kuliyapitiya, Sri Lanka
fYear :
2014
Firstpage :
272
Lastpage :
272
Abstract :
Clustering algorithms are used in wide varieties of fields in many contexts. In these cases the behavior of the datasets are different to each other. Their sizes, density or the distribution may vary from one another. In data mining, clustering algorithms are implemented to build clusters with respect to a given dataset. But it is not an easy task to find the most suitable clustering algorithm for the given dataset. Therefore this study is done on several datasets using four clustering algorithms to identify the most suitable algorithm. This study is based on comparison of clustering data mining algorithms by using WEKA machine learning software.
Keywords :
data mining; learning (artificial intelligence); pattern clustering; WEKA machine learning software; clustering algorithms; data mining;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advances in ICT for Emerging Regions (ICTer), 2014 International Conference on
Print_ISBN :
978-1-4799-7731-4
Type :
conf
DOI :
10.1109/ICTER.2014.7083930
Filename :
7083930
Link To Document :
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