吴昊, 唐振军. 加权壳近邻填充数学模型[J]. 华南师范大学学报(自然科学版), 2013, 45(3): 45-48.
引用本文: 吴昊, 唐振军. 加权壳近邻填充数学模型[J]. 华南师范大学学报(自然科学版), 2013, 45(3): 45-48.
Weighted Shell-Neighbor Imputation Methods[J]. Journal of South China Normal University (Natural Science Edition), 2013, 45(3): 45-48.
Citation: Weighted Shell-Neighbor Imputation Methods[J]. Journal of South China Normal University (Natural Science Edition), 2013, 45(3): 45-48.

加权壳近邻填充数学模型

Weighted Shell-Neighbor Imputation Methods

  • 摘要: 提出加权壳近邻填充缺失数据数学模型,充分利用壳近邻填充选取近邻数据的特性,侧重于被重复选择到的近邻点,有效提高了填充效果. 还提出一种称为goodness的新评价方法,克服了均方根误差(RMSE)的弱点. 实验结果表明,提出的加权壳近邻填充数学模型比一般的近邻填充的效果好,而且goodness评价方法比RMSE更能分辨出填充算法的性能.

     

    Abstract: Weighted methods are designed for improving Shell Neighbor Imputation, Called WSNI. They utilize the features of nearest neighbor selection of the WSNI. All multiple-selected nearest neighbors are stressed in the WSNI algorithms. This lads to pretty good performance.Experimental results show that the porposed algorithms have better performances than conventional neighbor imputation method.

     

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