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Multi-class Contour Preserving Classification

  • Piyabute Fuangkhon
  • Thitipong Tanprasert
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7435)

Abstract

The original contour preserving classification technique was proposed to improve the robustness and weight fault tolerance of a neural network applied with a two-class linearly separable problem. It was recently found to be improving the level of accuracy of two-class classification. This paper presents an augmentation of the original technique to improve the level of accuracy of multi-class classification by better preservation of the shape or distribution model of a multi-class problem. The test results on six real world multi-class datasets from UCI machine learning repository present that the proposed technique supports multi-class data and can improve the level of accuracy of multi-class classification more effectively.

Keywords

contour preserving classification data preprocessor neural network outpost vector pattern classification 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Piyabute Fuangkhon
    • 1
  • Thitipong Tanprasert
    • 1
  1. 1.Distributed and Parallel Computing Research Laboratory, Faculty of Science and TechnologyAssumption UniversityBangkokThailand

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