The week's pick
Reseach Article
Efficiency and Effectiveness of Clustering Algorithms for High Dimensional Data
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 125 - Number 11 |
| Year of Publication: 2015 |
| Authors: Smita Chormunge, Sudarson Jena |
10.5120/ijca2015906144
|
Smita Chormunge, Sudarson Jena . Efficiency and Effectiveness of Clustering Algorithms for High Dimensional Data. International Journal of Computer Applications. 125, 11 ( September 2015), 35-40. DOI=10.5120/ijca2015906144
Abstract
Clustering high dimensional data is challenging due to its dimensionality problem and it affects time complexity and accuracy of clustering methods. This paper presents the F-measure and Euclidean distance based performance efficiency and effectiveness of K-means and Agglomerative hierarchical clustering methods on Text and Microarray datasets by varying cluster values. Efficiency concerns about computational time required to build up dataset and effectiveness concerns about accuracy to cluster the data. Experimental results on different datasets demonstrate that K-means clustering algorithm is favourable in terms of effectiveness where as Agglomerative hierarchical clustering is efficient in time for text datasets used for empirical study.
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