Feature selection based on bagging ensemble learning algorithm

doi:10.1049/cp.2009.2058

IR > 计算机与通信学院

	Feature selection based on bagging ensemble learning algorithm
	Yan, Wang; Li, Wei Juan; Li, Rui; Wang, Xuyang
	2009
会议录名称	IET Conference Publications
卷号	2009
期号	562 CP
页码	734-736
出版者	Institution of Engineering and Technology
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.
关键词	Decision tables Feature extraction Learning systems Bagging Classification rules Count measure Ensemble learning Ensemble learning algorithm Generalization ability
DOI	10.1049/cp.2009.2058
收录类别	EI
语种	英语
EI入藏号	20105013473889
EI主题词	Learning algorithms
来源库	Compendex
分类代码	723.1 Computer Programming
引用统计	无
文献类型	会议论文
条目标识符	https://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
第一作者单位	兰州理工大学
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]:Institution of Engineering and Technology,2009:734-736.