GPSQL Miner: SQL-Grammar Genetic Programming in Data Mining

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  author =       "Celso Yoshikazu Ishida and 
                 Aurora Trinidad Ramirez Pozo",
  title =        "GPSQL Miner: SQL-Grammar Genetic Programming in Data
  booktitle =    "Proceedings of the 2002 Congress on Evolutionary
                 Computation CEC2002",
  editor =       "David B. Fogel and Mohamed A. El-Sharkawi and 
                 Xin Yao and Garry Greenwood and Hitoshi Iba and Paul Marrow and 
                 Mark Shackleton",
  pages =        "1226--1231",
  year =         "2002",
  publisher =    "IEEE Press",
  publisher_address = "445 Hoes Lane, P.O. Box 1331, Piscataway, NJ
                 08855-1331, USA",
  organisation = "IEEE Neural Network Council (NNC), Institution of
                 Electrical Engineers (IEE), Evolutionary Programming
                 Society (EPS)",
  ISBN =         "0-7803-7278-6",
  month =        "12-17 " # may,
  notes =        "CEC 2002 - A joint meeting of the IEEE, the
                 Evolutionary Programming Society, and the IEE. Held in
                 connection with the World Congress on Computational
                 Intelligence (WCCI 2002)",
  keywords =     "genetic algorithms, genetic programming, SQL, GPSQL
                 Miner, SQL-grammar genetic programming, data mining,
                 relational databases, grammars",
  DOI =          "doi:10.1109/CEC.2002.1004418",
  abstract =     "The present work describes GPSQL Miner, a Genetic
                 Programming system for mining relational databases.
                 This system uses Grammar Genetic Programming for
                 classification task and one of its main features is the
                 representation of the classifiers. The system uses SQL
                 grammar, which facilitates the evaluation process, once
                 the data are in relational databases. The tool was
                 tested with some databases and the results were
                 compared with other algorithms. These first experiments
                 had shown promising results for the classification

Genetic Programming entries for Celso Yoshikazu Ishida Aurora Trinidad Ramirez Pozo