Some Training Subset Selection Methods for Supervised Learning in Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@Unpublished{gathercole:1994:stss,
  author =       "Chris Gathercole and Peter Ross",
  title =        "Some Training Subset Selection Methods for Supervised
                 Learning in Genetic Programming",
  note =         "Presented at ECAI'94 Workshop on Applied Genetic and
                 other Evolutionary Algorithms",
  year =         "1994",
  keywords =     "genetic algorithms, genetic programming, LEF, DSS",
  URL =          "http://citeseer.ist.psu.edu/cache/papers/cs/733/ftp:zSzzSzftp.dai.ed.ac.ukzSzpubzSzuserzSzchrisgzSzchrisg_dss_paper_resubmitted_to_ecai94workshop.pdf/gathercole94some.pdf",
  URL =          "http://citeseer.ist.psu.edu/gathercole94some.html",
  abstract =     "When using the Genetic Programming (GP) Algorithm on a
                 difficult problem with a large set of training cases, a
                 large population size is needed and a very large number
                 of function-tree evaluations must be carried out. This
                 paper describes how to reduce the number of such
                 evaluations by selecting a small subset of the training
                 data set on which to actually carry out the GP
                 algorithm. Three subset selection methods described in
                 the paper are: Dynamic Subset Selection (DSS), using
                 the current...",
  size =         "13 pages",
}

Genetic Programming entries for Chris Gathercole Peter Ross

Citations