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Ant colony classification mining algorithm based on pheromone attraction and exclusion
Yang, Lei1; Li, Kangshun1; Zhang, Wensheng2; Ke, Zhenxu1
Source PublicationSOFT COMPUTING
2017-10-01
Volume21Issue:19Pages:5741-5753
SubtypeArticle
AbstractAnt colony optimization algorithms have been applied successfully in classification rule mining. However, basic ant colony classification mining algorithms generally suffer from problems, such as premature convergence and falling into local optimum easily. Simultaneously, the classification mining algorithms use sequential covering strategy to discover rules, and the interaction between rules is less considered. In this study, a new ant colony classification mining algorithm based on pheromone attraction and exclusion (Ant-Miner(PAE)) is proposed, in which a new pheromone calculation method is designed and the search is guided by the new probability transfer formula. By contrast, the basic algorithm structure is modified, and the order of the iteration is adjusted. Thus, the problem of rule interaction is mitigated. Ant-Miner(PAE) can balance the relation of exploration and development of constructing rules, which can make the ants in the search process initially explore and develop in the later period. Our experiments, which use 12 publicly available data sets, show that the predictive accuracy obtained by Ant-Miner(PAE) implementing the proposed pheromone attraction and exclusion strategy is statistically significantly higher than the predictive accuracy of other rule induction classification algorithms, such as CN2, C4.5 rules, PSO/AC-O2, Ant-Miner, and cAnt-Miner(PB). Furthermore, the rules discovered by Ant-Miner(PAE) are considerably simpler than those discovered by its counterparts.
KeywordData Mining Classification Rule Ant Colony Algorithm Pheromone Attraction And Exclusion
WOS HeadingsScience & Technology ; Technology
DOI10.1007/s00500-016-2151-9
WOS KeywordILL-POSED PROBLEMS ; PARAMETER-IDENTIFICATION ; MULTIGRID METHOD ; OPTIMIZATION
Indexed BySCI
Language英语
Funding OrganizationScience and Technology Project of Guangdong Province of China(2015A020209119 ; National Natural Science Foundation of China(61573157) ; Natural Science Foundation of Guangdong Province of China(S2013040015755) ; 2014A020208087)
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Interdisciplinary Applications
WOS IDWOS:000411867700018
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/20735
Collection精密感知与控制研究中心_人工智能与机器学习
Affiliation1.South China Agr Univ, Coll Math & Informat, Guangzhou, Guangdong, Peoples R China
2.Chinese Acad Sci, Inst Automat, Beijing, Peoples R China
Recommended Citation
GB/T 7714
Yang, Lei,Li, Kangshun,Zhang, Wensheng,et al. Ant colony classification mining algorithm based on pheromone attraction and exclusion[J]. SOFT COMPUTING,2017,21(19):5741-5753.
APA Yang, Lei,Li, Kangshun,Zhang, Wensheng,&Ke, Zhenxu.(2017).Ant colony classification mining algorithm based on pheromone attraction and exclusion.SOFT COMPUTING,21(19),5741-5753.
MLA Yang, Lei,et al."Ant colony classification mining algorithm based on pheromone attraction and exclusion".SOFT COMPUTING 21.19(2017):5741-5753.
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