International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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Volume 49 - Issue 6 |
Published: July 2012 |
Authors: Richa Loohach, Kanwal Garg |
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Richa Loohach, Kanwal Garg . Effect of Distance Functions on Simple K-means Clustering Algorithm. International Journal of Computer Applications. 49, 6 (July 2012), 7-9. DOI=10.5120/7629-0698
@article{ 10.5120/7629-0698, author = { Richa Loohach,Kanwal Garg }, title = { Effect of Distance Functions on Simple K-means Clustering Algorithm }, journal = { International Journal of Computer Applications }, year = { 2012 }, volume = { 49 }, number = { 6 }, pages = { 7-9 }, doi = { 10.5120/7629-0698 }, publisher = { Foundation of Computer Science (FCS), NY, USA } }
%0 Journal Article %D 2012 %A Richa Loohach %A Kanwal Garg %T Effect of Distance Functions on Simple K-means Clustering Algorithm%T %J International Journal of Computer Applications %V 49 %N 6 %P 7-9 %R 10.5120/7629-0698 %I Foundation of Computer Science (FCS), NY, USA
Clustering analysis is the most significant step in data mining. This paper discusses the k-means clustering algorithm and various distance functions used in k-means clustering algorithm such as Euclidean distance function and Manhattan distance function. Experimental results are shown to observe the effect of Manhattan distance function and Euclidean distance function on k-means clustering algorithm. These results also show that distance functions furthermore affect the size of clusters formed by the k-means clustering algorithm.