- 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)",
