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	Missing data treatment methods and NBI model
	Liu, Peng; Lei, Lei
	2006
页码	633-638
英文摘要	After reviewing missing mechanism, methods classification, and several well known treatment methods for missing data handling, this paper proposes a new method NBI. Naive Bayesian Imputation. NBI models use the imputation attribute as class attribute to build NBC. In this way, the imputation problem is turned into classification problem. NBC is insensitive to missing data and can be improved by attribute selection strategy. Extensive experiments on datasets from UCI are conducted to assess the effectiveness of NBI.
会议录出版者	IEEE COMPUTER SOC
会议录出版地	10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1264 USA
语种	英语
WOS研究方向	Computer Science
WOS记录号	WOS:000242507000116
内容类型	会议论文
源URL	[http://10.2.47.112/handle/2XS4QKH4/3489]
专题	上海财经大学
作者单位	Shanghai Univ Finance & Econ, Sch Informat Management & Engn, Shanghai, Peoples R China
推荐引用方式 GB/T 7714	Liu, Peng,Lei, Lei. Missing data treatment methods and NBI model[C]. 见:.

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