3. Voting Scheme–Based Evolutionary Kernel Machines for Drug Activity Comparisons

  1. Xiaohua Hu1 and
  2. Yi Pan2
  1. Bo Jin and
  2. Yan-Qing Zhang

Published Online: 23 MAY 2007

DOI: 10.1002/9780470124642.ch3

Knowledge Discovery in Bioinformatics: Techniques, Methods, and Applications

Knowledge Discovery in Bioinformatics: Techniques, Methods, and Applications

How to Cite

Jin, B. and Zhang, Y.-Q. (2007) Voting Scheme–Based Evolutionary Kernel Machines for Drug Activity Comparisons, in Knowledge Discovery in Bioinformatics: Techniques, Methods, and Applications (eds X. Hu and Y. Pan), John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/9780470124642.ch3

Editor Information

  1. 1

    College of Information Science and Technology, Drexel University, Philadelphia, PA 19104, USA

  2. 2

    Department of Computer Science, Georgia State University, Atlanta, GA 30302-4110, USA

Author Information

  1. Department of Computer Science, Georgia State University, Atlanta, GA 30302-4110, USA

Publication History

  1. Published Online: 23 MAY 2007
  2. Published Print: 25 MAY 2007

ISBN Information

Print ISBN: 9780471777960

Online ISBN: 9780470124642

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Keywords:

  • voting scheme–based evolutionary kernel machines (EVKMs);
  • evolutionary voting kernel machines;
  • evolutionary granular kernel tree (EGKT)

Summary

This chapter contains sections titled:

  • Granular Kernel and Kernel Tree Design

  • GKTSESs

  • Evolutionary Voting Kernel Machines

  • Simulations

  • Conclusions and Future Work

  • Acknowledgments

  • References