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Comparison of bias-variance structure of three classification algorithms:MCLP, LDA and C5.0

  • ZHU Mei-Hong ,
  • SHI Yong ,
  • LI Ai-Hua ,
  • ZHANG Dong-Ling
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  • 1. Graduate University of the Chinese Academy of Sciences, Beijing 100080, China;
    2. Research Center on Fictitious Economy & Data Sciences, Chinese Academy of Sciences, Beijing 100080, China;
    3. School of Statistics, Capital University of Economics and Business, Beijing 100070, China;
    4. School of Management Science and Engineering, Central University of Finance and Economics, Beijing 100081, China

Received date: 2008-11-17

  Revised date: 2009-03-02

  Online published: 2009-07-15

Abstract

Based on Domingos bias-variance decomposition framework, on three different data sets, we compared the bias-variance structure of the three classification methods: MCLP, LDA and C5.0. The experimental results showed that, generally speaking, C5.0 has low bias and high variance, LDA has high bias and low variance, and MCLP is in between them but near LDA. When the training set is small, bias and variance of MCLP is comparatively high. However, with the increasing of training set, bias and variance of MCLP obviously decrease and even are lower than those of C5.0 and LDA. This study established the basis for constructing the ensemble suited to MCLP.

Cite this article

ZHU Mei-Hong , SHI Yong , LI Ai-Hua , ZHANG Dong-Ling . Comparison of bias-variance structure of three classification algorithms:MCLP, LDA and C5.0[J]. Journal of University of Chinese Academy of Sciences, 2009 , 26(4) : 443 -450 . DOI: 10.7523/j.issn.2095-6134.2009.4.003

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