Best SubTree genetic programming

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

@InProceedings{1277287,
  author =       "Oana Muntean and Laura Diosan and Mihai Oltean",
  title =        "Best SubTree genetic programming",
  booktitle =    "GECCO '07: Proceedings of the 9th annual conference on
                 Genetic and evolutionary computation",
  year =         "2007",
  editor =       "Dirk Thierens and Hans-Georg Beyer and 
                 Josh Bongard and Jurgen Branke and John Andrew Clark and 
                 Dave Cliff and Clare Bates Congdon and Kalyanmoy Deb and 
                 Benjamin Doerr and Tim Kovacs and Sanjeev Kumar and 
                 Julian F. Miller and Jason Moore and Frank Neumann and 
                 Martin Pelikan and Riccardo Poli and Kumara Sastry and 
                 Kenneth Owen Stanley and Thomas Stutzle and 
                 Richard A Watson and Ingo Wegener",
  volume =       "2",
  isbn13 =       "978-1-59593-697-4",
  pages =        "1667--1673",
  address =      "London",
  URL =          "http://www.cs.bham.ac.uk/~wbl/biblio/gecco2007/docs/p1667.pdf",
  DOI =          "doi:10.1145/1276958.1277287",
  publisher =    "ACM Press",
  publisher_address = "New York, NY, USA",
  month =        "7-11 " # jul,
  organisation = "ACM SIGEVO (formerly ISGEC)",
  keywords =     "genetic algorithms, genetic programming, regression,
                 subtree",
  abstract =     "The result of the program encoded into a Genetic
                 Programming (GP) tree is usually returned by the root
                 of that tree. However, this is not a general strategy.
                 In this paper we present and investigate a new variant
                 where the best subtree is chosen to provide the
                 solution of the problem. The other nodes (not belonging
                 to the best subtree) are deleted. This will reduce the
                 size of the chromosome in those cases where its best
                 subtree is different from the entire tree. We have
                 tested this strategy on a wide range of regression and
                 classification problems. Numerical experiments have
                 shown that the proposed approach can improve both the
                 search speed and the quality of results.",
  notes =        "GECCO-2007 A joint meeting of the sixteenth
                 international conference on genetic algorithms
                 (ICGA-2007) and the twelfth annual genetic programming
                 conference (GP-2007).

                 ACM Order Number 910071",
}

Genetic Programming entries for Oana Muntean Laura Diosan Mihai Oltean

Citations