Estimation of Missing Values Using a Weighted K-Nearest Neighbors Algorithm

Authors:
Wang Ling;Fu Dong-Mei
Affiliations:
-;-
Venue:
ESIAT '09 Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 03
Year:
2009

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Abstract

This paper developed a novel method to estimate the values of missing data by the use of a weighted -nearest neighbors algorithm. A weighting scheme that exploits the correlation between a “missing” dimension and available data values from other fields, which is quantified based on the support vector regression method. The proposed method has been applied to a practical case of modeling steel corrosion. Comparing with the traditional imputation algorithm, the model results demonstrate its better generalization capability.