Application of Genetic Programming to Induction of Linear Classification Trees

Created by W.Langdon from gp-bibliography.bib Revision:1.1944

@InProceedings{bot:2000:GPilct,
  author =       "Martijn C. J. Bot and William B. Langdon",
  title =        "Application of Genetic Programming to Induction of
                 Linear Classification Trees",
  booktitle =    "Genetic Programming, Proceedings of EuroGP'2000",
  year =         "2000",
  editor =       "Riccardo Poli and Wolfgang Banzhaf and 
                 William B. Langdon and Julian F. Miller and Peter Nordin and 
                 Terence C. Fogarty",
  volume =       "1802",
  series =       "LNCS",
  pages =        "247--258",
  address =      "Edinburgh",
  publisher_address = "Berlin",
  month =        "15-16 " # apr,
  organisation = "EvoNet",
  publisher =    "Springer-Verlag",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "3-540-67339-3",
  URL =          "http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/martijn/bot.eurogp2000.19jan.ps.gz",
  URL =          "http://citeseer.ist.psu.edu/318695.html",
  URL =          "http://www.springerlink.com/openurl.asp?genre=article&issn=0302-9743&volume=1802&spage=247",
  doi =          "doi:10.1007/978-3-540-46239-2_18",
  abstract =     "A common problem in datamining is to find accurate
                 classifiers for a dataset. For this purpose, genetic
                 programming (GP) is applied to a set of benchmark
                 classification problems. Using GP we are able to induce
                 decision trees with a linear combination of variables
                 in each function node. A new representation of decision
                 trees using strong typing in GP is introduced. With
                 this representation it is possible to let the GP
                 classify into any number o f classes. Results indicate
                 that GP can be applied successfully to classification
                 problems. Comparisons with current state-of-the-art
                 algorithms in machine learning are presented and areas
                 of future research are identified.",
  notes =        "See also \cite{bot:1999:GPilct} EuroGP'2000, part of
                 \cite{poli:2000:GP}",
}

Genetic Programming entries for Martijn C J Bot William B Langdon