基于支持向量机的缺失数据处理方法

2011 International Conference on System science, Engineering design and Manufacturing informatization Pub Date : 2011-11-18 DOI:10.1109/ICSSEM.2011.6081198

Yang Li-hua, Ni Qing-hua

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引用次数: 0

摘要

本文系统地分析了缺失数据产生的原因和机制，研究了基于支持向量机的缺失数据处理方法。结果表明，基于支持向量机方法的预测效果优于神经网络、小波网络模型。该方法可以在一定程度上促进和应用于缺失数据的预测。

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Based on support vector machine approach to missing data

This paper systematically analyzes the causes and the mechanism of missing data, and research the processing method of missing data based on the support vector machine. And the results show that the prediction based on support vector machine method is more desirable than neural network, wavelet network model. And this method can promote and apply in the prediction of missing data to a certain extend.

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2011 International Conference on System science, Engineering design and Manufacturing informatization

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