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Genetically designed multiple-kernels for improving the SVM performance

Published: 07 July 2007 Publication History

Abstract

Classical kernel-based classifiers only use a single kernel, butthe real world applications have emphasized the need to con-sider a combination of kernels also known as a multiple kernel in order to boost the performance. Our purpose isto automatically find the mathematical expression of a multiple kernel by evolutionary means. In order to achieve this purpose we propose a hybrid model that combines a Genetic Programming (GP) algorithm and a kernel-based Support Vector Machine (SVM) classifier. Each GP chromosome isa tree encoding the mathematical expression of a multiple kernel. Numerical experiments show that the SVM embedding the evolved multiple kernel performs better than the standard kernels for the considered classification problems.

References

[1]
C. Cortes and V. Vapnik. Support-vector networks. Machine Learning, 20:273--297, 1995.
[2]
J. R. Koza. Genetic Programming: On the Programming of Computers by Means of Natural Selection. MIT Press, Cambridge, MA, USA, 1992.
[3]
B. Schoelkopf and A. J. Smola. Learning with Kernels. The MIT Press, Cambridge, MA, 2002.
[4]
V. Vapnik. The Nature of Statistical Learning Theory. Springer Verlag, New York, 1995.

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cover image ACM Conferences
GECCO '07: Proceedings of the 9th annual conference on Genetic and evolutionary computation
July 2007
2313 pages
ISBN:9781595936974
DOI:10.1145/1276958

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 07 July 2007

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Author Tags

  1. SVM
  2. genetic programming
  3. kernel

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GECCO07
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GECCO '07 Paper Acceptance Rate 266 of 577 submissions, 46%;
Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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  • (2017)A Novel Vision-Based Classification System for Explosion PhenomenaJournal of Imaging10.3390/jimaging30200143:2(14)Online publication date: 15-Apr-2017
  • (2011)A general frame for building optimal multiple SVM kernelsProceedings of the 8th international conference on Large-Scale Scientific Computing10.1007/978-3-642-29843-1_29(256-263)Online publication date: 6-Jul-2011
  • (2010)Object Categorization Using Genetic ProgrammingProceedings of the 2010 Fourth International Conference on Genetic and Evolutionary Computing10.1109/ICGEC.2010.80(297-300)Online publication date: 13-Dec-2010
  • (2009)Optimization of complex SVM kernels using a hybrid algorithm based on wasp behaviourProceedings of the 7th international conference on Large-Scale Scientific Computing10.1007/978-3-642-12535-5_42(361-368)Online publication date: 4-Jun-2009
  • (2007)A Hybrid Genetic Programming and Boosting Technique for Learning Kernel Functions from Training DataProceedings of the Ninth International Symposium on Symbolic and Numeric Algorithms for Scientific Computing10.1109/SYNASC.2007.71(395-402)Online publication date: 26-Sep-2007

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