Feature selection based on bagging ensemble learning algorithm

doi:10.1049/cp.2009.2058

	Feature selection based on bagging ensemble learning algorithm
	Yan, Wang; Li, Wei Juan; Li, Rui; Wang, Xuyang
	2009
关键词	Decision tables Feature extraction Learning systems Bagging Classification rules Count measure Ensemble learning Ensemble learning algorithm Generalization ability
卷号	2009
期号	562 CP
DOI	10.1049/cp.2009.2058
页码	734-736
英文摘要	Generalization ability is a principal issue in the field of machine learning. Feature selection is a method that can improve generalization ability of learning algorithm. Through measuring feature count measure (FCM)decision table, select the feature which depended strongly on classification attribute. Based on the above, Feature count measure based bagging ensemble learning algorithm is proposed. Experiment results show that the proposed algorithm is effective to obtain classification rule.
会议录	IET Conference Publications
会议录出版者	Institution of Engineering and Technology
语种	英语
内容类型	会议论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/116626]
专题	计算机与通信学院兰州理工大学
作者单位	College of Computer and Communication, Lanzhou University of Technology, Lanzhou, Gansu 730050, China
推荐引用方式 GB/T 7714	Yan, Wang,Li, Wei Juan,Li, Rui,et al. Feature selection based on bagging ensemble learning algorithm[C]. 见:.