AntPart: an algorithm for the unsupervised classification problem using ants

被引:14
|
作者
Admane, Lotfi [1 ]
Benatchba, Karima [1 ]
Koudil, Mouloud [1 ]
Siad, Lamn [1 ]
Maziz, Said [1 ]
机构
[1] Inst Natl Informat, Algiers, Algeria
关键词
data-mining; optimization; unsupervised classification; ant colonies;
D O I
10.1016/j.amc.2005.11.130
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
Unsupervised classification is one of the tasks of data-mining. In this paper, a method named AntPart for the resolution of exclusive unsupervised classification is introduced. It is inspired by the behavior of a particular species of ants called Pachycondyla apicalis. The performances of this method are compared with those of three other ones, also inspired by the social behavior of ants: AntClass, AntTree and AntClust. (c) 2006 Elsevier Inc. All rights reserved.
引用
收藏
页码:16 / 28
页数:13
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