한국데이터정보과학회:학술대회논문집
- 2006.04a
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- Pages.55-62
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- 2006
A Study on the Treatment of Missing Value using Grey Relational Grade and k-NN Approach
- Chun, Young-Min (Department of Statistical Information, Chonbuk National University) ;
- Chung, Sung-Suk (Division of Mathematics and Statistical Informatics, Chonbuk National University)
- Published : 2006.04.28
Abstract
Huang proposed a grey-based nearest neighbor approach to predict accurately missing attribute value in 2004. Our study proposes which way to decide the number of nearest neighbors using not only the dong's grey relational grade but also the wen's grey relational grade. Besides, our study uses not an arithmetic(unweighted) mean but a weighted one. Also, GRG is used by a weighted value when we impute a missing values. There are four different methods - DU, DW, WU, WW. The performance of WW(wen's GRG & weighted mean) method is the best of my other methods. It had been proven by Huang that his method was much better than mean imputation method and multiple imputation method. The performance of our study is far superior to that of Huang.