Dynamic Training Subset Selection for Supervised Learning in Genetic Programming   [SL] [GP]

by

Gathercole, C. and Ross, P.

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Info: Parallel Problem Solving from Nature III (Conference proceedings), 1994, p. 312-321
Keywords:genetic algorithms, genetic programming
Abstract:
Desctibes how to reduce the number [TNO] of fitness case evaluations in difficult GP problems by selecting a small subset of the training data. Dynamic Subset Selection can produce better results than GP in less than 20% of the time. Population size [PS] of 5,000 and 10,000.
Notes:
PPSN3
URL(s):(G)zipped postscript

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BibTex:
@InProceedings{ga94aGathercole,
  author =       "Chris Gathercole and Peter Ross",
  title =        "Dynamic Training Subset Selection for Supervised
                 Learning in Genetic Programming",
  booktitle =    "Parallel Problem Solving from Nature III",
  year =         "1994",
  editor =       "Yuval Davidor and Hans-Paul Schwefel and Reinhard
                 M{\"a}nner",
  pages =        "312--321",
  address =      "Jerusalem",
  publisher_address = "Berlin, Germany",
  month =        "9-14 " # oct,
  publisher =    "Springer-Verlag",
  keywords =     "genetic algorithms, genetic programming",
  URL =          "ftp://ftp.dai.ed.ac.uk/pub/ga/94-006.ps.Z",
  abstract =     "Desctibes how to reduce the number of fitness case
                 evaluations in difficult GP problems by selecting a
                 small subset of the training data. Dynamic Subset
                 Selection can produce better results than GP in less
                 than 20% of the time. Population size of 5,000 and
                 10,000.",
  notes =        "PPSN3",
}