Combining Discriminant Models with New Multi-Class SVMs

@article{Guermeur2002CombiningDM,
  title={Combining Discriminant Models with New Multi-Class SVMs},
  author={Yann Guermeur},
  journal={Pattern Analysis & Applications},
  year={2002},
  volume={5},
  pages={168-179}
}
The idea of performing model combination, instead of model selection, has a long theoretical background in statistics. However, making use of theoretical results is ordinarily subject to the satisfaction of strong hypotheses (weak error correlation, availability of large training sets, possibility to rerun the training procedure an arbitrary number of times, etc.). In contrast, the practitioner is frequently faced with the problem of combining a given set of pre-trained classifiers, with highly… CONTINUE READING
Highly Influential
This paper has highly influenced 11 other papers. REVIEW HIGHLY INFLUENTIAL CITATIONS

Citations

Publications citing this paper.
Showing 1-10 of 63 extracted citations

References

Publications referenced by this paper.
Showing 1-10 of 85 references

Estimation of Dependences

  • VN Vapnik
  • Based on Empirical Data. Springer-Verlag,
  • 1982
Highly Influential
13 Excerpts

Etude de la complexité et contrôle de la capacité des systèmes d’apprentissage: SVM multi-classe, réseaux de régularisation et réseaux de neurones multicouches

  • A. Elisseeff
  • PhD thesis, ENS Lyon,
  • 2000
Highly Influential
5 Excerpts

Bounding the capacity measure of multi-class discriminant models

  • Y Guermeur, A Elisseeff, D. Zelus
  • Technical report, NC2-TR2002-123,
  • 2002
Highly Influential
4 Excerpts

Combinaison de classifieurs statistiques, application à la prédiction de la structure secondaire des protéines

  • Y. Guermeur
  • PhD thesis, Université Paris
  • 1997
Highly Influential
6 Excerpts

Similar Papers

Loading similar papers…