Inductive Genetic Programming with Decision Trees

Created by W.Langdon from gp-bibliography.bib Revision:1.4192

  author =       "Nikolay I. Nikolaev and Vanio Slavov",
  title =        "Inductive Genetic Programming with Decision Trees",
  booktitle =    "9th European Conference on Machine Learning",
  year =         "1997",
  editor =       "Maarten {van Someren} and Gerhard Widmer",
  volume =       "1224",
  series =       "Lecture Notes in Computer Science",
  pages =        "183--190",
  address =      "Prague, Czech Republic",
  month =        "23-26 " # apr,
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming, Computer
  isbn13 =       "978-3-540-62858-3",
  broken =       "",
  DOI =          "doi:10.1007/3-540-62858-4_83",
  size =         "8 pages",
  abstract =     "This paper proposes an empirical study of inductive
                 Genetic Programming with Decision Trees. An approach to
                 development of fitness functions for efficient
                 navigation of the search process is presented. It
                 relies on analysis of the fitness landscape structure
                 and suggests measuring its characteristics with
                 statistical correlations. We demonstrate that this
                 approach increases the global landscape correlation,
                 and thus leads to mitigation of the search
                 difficulties. Another claim is that the elaborated
                 fitness functions help to produce decision trees with
                 low syntactic complexity and high predictive
  notes =        "ECML-97",
  affiliation =  "American University in Bulgaria Department of Computer
                 Science 2700 Blagoevgrad Bulgaria",

Genetic Programming entries for Nikolay Nikolaev Vanio Slavov