Bag of little bootstraps on features for enhancing classification performance

doi:10.3233/IDA-160857

	Bag of little bootstraps on features for enhancing classification performance
	Wang, Haocheng 1,2; Zhuang, Fuzhen 1; Jin, Xin 3; Ao, Xiang 1; He, Qing 1
	2016
发表期刊	INTELLIGENT DATA ANALYSIS
ISSN	1088-467X
卷号	20 期号:5 页码:1085-1099
摘要	Ensemble learning via manipulating the training set is an effective technique for improving classification accuracy. In this work, we investigate the strategy how to combine learning set resampling method and random subspace method applied in high-dimensional domains. We propose a new procedure, Bag of Little Bootstraps on Features (BLBF), which works by combining the results of bootstrapping multiple feature subsets of the original dataset using the random subspace method. Our empirical experiments on various high-dimensional datasets demonstrate that our proposed approach outperforms the state-of-the-art instance-based resampling learning algorithm BLB and its two relevant variants, in terms of classification performance. In addition, we also investigate the effect of hyperparameters on classification performance, which shows that the parameters can be easily set while maintaining a good performance.
关键词	Ensemble learning bag of little bootstraps on features high-dimensional data classification
DOI	10.3233/IDA-160857
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[91546122] ; National Natural Science Foundation of China[61573335] ; National Natural Science Foundation of China[61473273] ; National Natural Science Foundation of China[61473274] ; National High-tech R&D Program of China (863 Program)[2014AA015105] ; Guangdong provincial science and technology plan projects[2015 B010109005]
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence
WOS记录号	WOS:000384428500006
出版者	IOS PRESS
引用统计	被引频次：1[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/8137
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Wang, Haocheng
作者单位	1.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing, Peoples R China 2.Univ Chinese Acad Sci, Beijing, Peoples R China 3.Huawei Technol Co Ltd, Cent Software Inst, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Wang, Haocheng,Zhuang, Fuzhen,Jin, Xin,et al. Bag of little bootstraps on features for enhancing classification performance[J]. INTELLIGENT DATA ANALYSIS,2016,20(5):1085-1099.
APA	Wang, Haocheng,Zhuang, Fuzhen,Jin, Xin,Ao, Xiang,&He, Qing.(2016).Bag of little bootstraps on features for enhancing classification performance.INTELLIGENT DATA ANALYSIS,20(5),1085-1099.
MLA	Wang, Haocheng,et al."Bag of little bootstraps on features for enhancing classification performance".INTELLIGENT DATA ANALYSIS 20.5(2016):1085-1099.