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