AntPart: an algorithm for the unsupervised classification problem using ants

被引：15

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

来源：

APPLIED MATHEMATICS AND COMPUTATION | 2006年 / 180卷 / 01期

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

页码：16 / 28

页数：13

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