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Application of Conformal Predictors to Tea Classification Based on Electronic Nose

  • Ilia Nouretdinov
  • Guang Li
  • Alexander Gammerman
  • Zhiyuan Luo
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 339)

Abstract

In this paper, we present an investigation into the performance of conformal predictors for discriminating the aroma of different types of tea using an electronic nose system based on gas sensors. We propose a new non-conformity measure for the implementation of conformal predictors based on Support Vector Machine for multi-class classification problems. The experimental results have shown the good performance of the implemented conformal predictors.

Keywords

Tea Classification Electronic Nose Conformal Predictors Support Vector Machines Pattern Recognition 

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Copyright information

© IFIP 2010

Authors and Affiliations

  • Ilia Nouretdinov
    • 1
  • Guang Li
    • 2
  • Alexander Gammerman
    • 1
  • Zhiyuan Luo
    • 1
  1. 1.Computer Learning Research Centre, Royal HollowayUniversity of LondonSurreyUK
  2. 2.Department of Control Science and EngineeringZhejiang UniversityZhejiangP.R. China

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