International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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Volume 29 - Issue 7 |
Published: September 2011 |
Authors: Mohammad F. Eltibi, Wesam M. Ashour |
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Mohammad F. Eltibi, Wesam M. Ashour . Initializing K-Means Clustering Algorithm using Statistical Information. International Journal of Computer Applications. 29, 7 (September 2011), 51-55. DOI=10.5120/3573-4930
@article{ 10.5120/3573-4930, author = { Mohammad F. Eltibi,Wesam M. Ashour }, title = { Initializing K-Means Clustering Algorithm using Statistical Information }, journal = { International Journal of Computer Applications }, year = { 2011 }, volume = { 29 }, number = { 7 }, pages = { 51-55 }, doi = { 10.5120/3573-4930 }, publisher = { Foundation of Computer Science (FCS), NY, USA } }
%0 Journal Article %D 2011 %A Mohammad F. Eltibi %A Wesam M. Ashour %T Initializing K-Means Clustering Algorithm using Statistical Information%T %J International Journal of Computer Applications %V 29 %N 7 %P 51-55 %R 10.5120/3573-4930 %I Foundation of Computer Science (FCS), NY, USA
K-means clustering algorithm is one of the best known algorithms used in clustering; nevertheless it has many disadvantages as it may converge to a local optimum, depending on its random initialization of prototypes. We will propose an enhancement to the initialization process of k-means, which depends on using statistical information from the data set to initialize the prototypes. We show that our algorithm gives valid clusters, and that it decreases error and time.