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Model Selection for Support Vector Machines


Conference Paper


New functionals for parameter (model) selection of Support Vector Machines are introduced based on the concepts of the span of support vectors and rescaling of the feature space. It is shown that using these functionals, one can both predict the best choice of parameters of the model and the relative quality of performance for any value of parameter.

Author(s): Chapelle, O. and Vapnik, V.
Book Title: Advances in Neural Information Processing Systems 12
Journal: Advances in Neural Information Processing Systems
Pages: 230-236
Year: 2000
Month: June
Day: 0
Editors: Solla, S.A. , T.K. Leen, K-R M{\"u}ller
Publisher: MIT Press

Department(s): Empirical Inference
Bibtex Type: Conference Paper (inproceedings)

Event Name: Thirteenth Annual Neural Information Processing Systems Conference (NIPS 1999)
Event Place: Denver, CO, USA

Address: Cambridge, MA, USA
Digital: 0
ISBN: 0-262-19450-3
Organization: Max-Planck-Gesellschaft
School: Biologische Kybernetik

Links: PDF


  title = {Model Selection for Support Vector Machines},
  author = {Chapelle, O. and Vapnik, V.},
  journal = {Advances in Neural Information Processing Systems},
  booktitle = {Advances in Neural Information Processing Systems 12},
  pages = {230-236},
  editors = {Solla, S.A. , T.K. Leen, K-R M{\"u}ller},
  publisher = {MIT Press},
  organization = {Max-Planck-Gesellschaft},
  school = {Biologische Kybernetik},
  address = {Cambridge, MA, USA},
  month = jun,
  year = {2000},
  month_numeric = {6}