Structural Risk Minimization on Decision Trees Using An Evolutionary Multiobjective Optimization

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@InProceedings{kim:2004:eurogp,
  author =       "DaeEun Kim",
  title =        "Structural Risk Minimization on Decision Trees Using
                 An Evolutionary Multiobjective Optimization",
  booktitle =    "Genetic Programming 7th European Conference, EuroGP
                 2004, Proceedings",
  year =         "2004",
  editor =       "Maarten Keijzer and Una-May O'Reilly and 
                 Simon M. Lucas and Ernesto Costa and Terence Soule",
  volume =       "3003",
  series =       "LNCS",
  pages =        "338--348",
  address =      "Coimbra, Portugal",
  publisher_address = "Berlin",
  month =        "5-7 " # apr,
  organisation = "EvoNet",
  publisher =    "Springer-Verlag",
  keywords =     "genetic algorithms, genetic programming: Poster",
  ISBN =         "3-540-21346-5",
  URL =          "http://www.springerlink.com/openurl.asp?genre=article&issn=0302-9743&volume=3003&spage=338",
  DOI =          "doi:10.1007/978-3-540-24650-3_32",
  abstract =     "Inducing decision trees is a popular method in machine
                 learning. The information gain computed for each
                 attribute and its threshold helps finding a small
                 number of rules for data classification. However, there
                 has been little research on how many rules are
                 appropriate for a given set of data. An evolutionary
                 multi-objective optimisation approach with genetic
                 programming will be applied to the data classification
                 problem in order to find the minimum error rate for
                 each size of decision trees. Following structural risk
                 minimisation suggested by Vapnik, we can determine a
                 desirable number of rules with the best generalisation
                 performance. A hierarchy of decision trees for
                 classification performance can be provided and it is
                 compared with C4.5 application.",
  notes =        "Part of \cite{keijzer:2004:GP} EuroGP'2004 held in
                 conjunction with EvoCOP2004 and EvoWorkshops2004",
}

Genetic Programming entries for DaeEun Kim

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