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@ARTICLE{Eitrich:48496,
      author       = {Eitrich, T. and Lang, B.},
      title        = {{E}fficient {O}ptimization of {S}upport {V}ector {M}achine
                      {L}earning {P}arameters for {U}nbalanced {D}ata {S}ets},
      journal      = {Journal of Computational and Applied Mathematics},
      volume       = {196},
      issn         = {0377-0427},
      address      = {Amsterdam [u.a.]},
      publisher    = {North-Holland},
      reportid     = {PreJuSER-48496},
      pages        = {425 - 436},
      year         = {2006},
      note         = {Record converted from VDB: 12.11.2012},
      abstract     = {Support vector machines are powerful kernel methods for
                      classification and regression tasks. If trained optimally,
                      they produce excellent separating hyperplanes. The quality
                      of the training, however, depends not only on the given
                      training data but also on additional learning parameters,
                      which are difficult to adjust, in particular for unbalanced
                      datasets. Traditionally, grid search techniques have been
                      used for determining suitable values for these parameters.
                      In this paper, we propose an automated approach to adjusting
                      the learning parameters using a derivative-free numerical
                      optimizer. To make the optimization process more efficient,
                      a new sensitive quality measure is introduced. Numerical
                      tests with a well-known dataset show that our approach can
                      produce support vector machines that are very well tuned to
                      their classification tasks. (c) 2005 Elsevier B.V. All
                      rights reserved.},
      keywords     = {J (WoSType)},
      cin          = {ZAM},
      ddc          = {510},
      cid          = {I:(DE-Juel1)VDB62},
      pnm          = {Scientific Computing},
      pid          = {G:(DE-Juel1)FUEK411},
      shelfmark    = {Mathematics, Applied},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000239746800007},
      doi          = {10.1016/j.cam.2005.09.009},
      url          = {https://juser.fz-juelich.de/record/48496},
}