Pruning association rules using statistics and genetic relation algoritm

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{Gonzales:2010:gecco,
  author =       "Eloy Gonzales and Shingo Mabu and Karla Taboada and 
                 Kotaro Hirasawa and Kaoru Shimada",
  title =        "Pruning association rules using statistics and genetic
                 relation algoritm",
  booktitle =    "GECCO '10: Proceedings of the 12th annual conference
                 on Genetic and evolutionary computation",
  year =         "2010",
  editor =       "Juergen Branke and Martin Pelikan and Enrique Alba and 
                 Dirk V. Arnold and Josh Bongard and 
                 Anthony Brabazon and Juergen Branke and Martin V. Butz and 
                 Jeff Clune and Myra Cohen and Kalyanmoy Deb and 
                 Andries P Engelbrecht and Natalio Krasnogor and 
                 Julian F. Miller and Michael O'Neill and Kumara Sastry and 
                 Dirk Thierens and Jano {van Hemert} and Leonardo Vanneschi and 
                 Carsten Witt",
  isbn13 =       "978-1-4503-0072-8",
  pages =        "419--420",
  keywords =     "genetic algorithms, genetic programming, Evolution
                 strategies and evolutionary programming, Poster",
  month =        "7-11 " # jul,
  organisation = "SIGEVO",
  address =      "Portland, Oregon, USA",
  DOI =          "doi:10.1145/1830483.1830562",
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  abstract =     "Most of the classification methods proposed produces
                 too many rules for humans to read over, that is, the
                 number of generated rules is thousands or millions
                 which means complex and hardly understandable for the
                 users.

                 In this paper, a new post-processing pruning method for
                 class association rules is proposed by a combination of
                 statistics and an evolutionary method named Genetic
                 Relation Algorithm (GRA). The algorithm is carried out
                 in two phases. In the first phase the rules are pruned
                 depending on their matching degree and in the second
                 phase GRA selects the most interesting rules using the
                 distance between them and their strength.",
  notes =        "Also known as \cite{1830562} GECCO-2010 A joint
                 meeting of the nineteenth international conference on
                 genetic algorithms (ICGA-2010) and the fifteenth annual
                 genetic programming conference (GP-2010)",
}

Genetic Programming entries for Eloy Gonzales Shingo Mabu Karla Taboada Kotaro Hirasawa Kaoru Shimada

Citations