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  • 标题:Missing Value Imputation using Refined Mean Substitution
  • 本地全文:下载
  • 作者:R. S. Somasundaram ; R. Nedunchezhian
  • 期刊名称:International Journal of Computer Science Issues
  • 印刷版ISSN:1694-0784
  • 电子版ISSN:1694-0814
  • 出版年度:2012
  • 卷号:9
  • 期号:4
  • 出版社:IJCSI Press
  • 摘要:In a previous work, it was clearly shown that the performance of the very simple imputation method based on Most Common Attribute Value called MC gave performance better than that of several complex imputation algorithms. And in that work [1] it was shown that the performance of MC was almost equal to that of best performing imputation method called Event Covering (EC). So in this work, It is tried to improve the performance of the simple imputation method MC and proposed a new algorithm. The performance of the proposed algorithm has been compared with the other simple and efficient imputation methods. The performance has been measured with respect to different rate or different percentage of missing values in the data set. To evaluate the performance, the standard WDBC data set has been used. The proposed algorithm performed very well and the arrived results were more significant and comparable.
  • 关键词:Datamining; Preprocessing; Missing Value
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