Journal of the Korean Data and Information Science Society

The Korean Data and Information Science Society (한국데이터정보과학회)
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A Modified Grey-Based k-NN Approach for Treatment of Missing Value

  • Chun, Young-M. (Department of Statistical Informatics, Chonbuk National University) ;
  • Lee, Joon-W. (Division of Electronics and Information Engineering, Chonbuk National University) ;
  • Chung, Sung-S. (Division of Mathematics and Statistical Informatics, Chonbuk National University)
  • Published : 2006.05.30
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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 deng'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 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 any 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.

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