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	A unified strategy of feature selection
	Liu, Peng; Wu, Naijun; Zhu, Jiaxian; Yin, Junjie; Zhang, Wei
	2006
卷号	4093
页码	457-464
英文摘要	In the field of data mining (DM), feature selection is one of the basic strategies handling with high-dimensionality problems. This paper makes a review of current methods of feature selection and proposes a unified strategy of feature selection, which divides overall procedures of feature selection into two stages, first to determine the FIF (Feature Important Factor) of features according to DM tasks, second to select features according to FIF. For classifying problems, we propose a new method for determining FIF based on decision trees and provide practical suggestion for feature selection. Through analysis on experiments conducted on UCI datasets, such a unified strategy of feature selection is proven to be effective and efficient.
会议录出版者	SPRINGER-VERLAG BERLIN
会议录出版地	HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY
语种	英语
WOS研究方向	Computer Science
WOS记录号	WOS:000240088200050
内容类型	会议论文
源URL	[http://10.2.47.112/handle/2XS4QKH4/3303]
专题	上海财经大学
作者单位	Shanghai Univ Finance & Econ, Sch Informat Management & Engn, Shanghai 200433, Peoples R China
推荐引用方式 GB/T 7714	Liu, Peng,Wu, Naijun,Zhu, Jiaxian,et al. A unified strategy of feature selection[C]. 见:.

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