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Initializing K-Means Clustering Algorithm using Statistical Information

by Mohammad F. Eltibi, Wesam M. Ashour
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 29 - Number 7
Year of Publication: 2011
Authors: Mohammad F. Eltibi, Wesam M. Ashour
10.5120/3573-4930

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 },
issue_date = { September 2011 },
volume = { 29 },
number = { 7 },
month = { September },
year = { 2011 },
issn = { 0975-8887 },
pages = { 51-55 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume29/number7/3573-4930/ },
doi = { 10.5120/3573-4930 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:15:13.043867+05:30
%A Mohammad F. Eltibi
%A Wesam M. Ashour
%T Initializing K-Means Clustering Algorithm using Statistical Information
%J International Journal of Computer Applications
%@ 0975-8887
%V 29
%N 7
%P 51-55
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

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.

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Index Terms

Computer Science
Information Sciences

Keywords

Clustering K-means Clustering Initial Prototypes Determination Central Limit Theory Normal Distribution Maximum Likelihood Estimator

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