Research Article
Article:Unsupervised Classification Using Immune Algorithm
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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| Volume 2 - Issue 7 |
| Published: June 2010 |
| Authors: M.T. Al-Muallim, R. El-Kouatly |
10.5120/677-952
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M.T. Al-Muallim, R. El-Kouatly . Article:Unsupervised Classification Using Immune Algorithm. International Journal of Computer Applications. 2, 7 (June 2010), 44-48. DOI=10.5120/677-952
@article{ 10.5120/677-952,
author = { M.T. Al-Muallim,R. El-Kouatly },
title = { Article:Unsupervised Classification Using Immune Algorithm },
journal = { International Journal of Computer Applications },
year = { 2010 },
volume = { 2 },
number = { 7 },
pages = { 44-48 },
doi = { 10.5120/677-952 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2010
%A M.T. Al-Muallim
%A R. El-Kouatly
%T Article:Unsupervised Classification Using Immune Algorithm%T
%J International Journal of Computer Applications
%V 2
%N 7
%P 44-48
%R 10.5120/677-952
%I Foundation of Computer Science (FCS), NY, USA
Abstract
Unsupervised classification algorithm based on clonal selection principle named Unsupervised Clonal Selection Classification (UCSC) is proposed in this paper. The new proposed algorithm is data driven and self-adaptive, it adjusts its parameters to the data to make the classification operation as fast as possible. The performance of UCSC is evaluated by comparing it with the well known K-means algorithm using several artificial and real-life data sets. The experiments show that the proposed UCSC algorithm is more reliable and has high classification precision comparing to traditional classification methods such as K-means.
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