A Genetic Programming Framework for Two Data Mining Tasks: Classification and Generalized Rule Induction

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

@InProceedings{Freitas:1997:GPf2dm,
  author =       "Alex A. Freitas",
  title =        "A Genetic Programming Framework for Two Data Mining
                 Tasks: Classification and Generalized Rule Induction",
  booktitle =    "Genetic Programming 1997: Proceedings of the Second
                 Annual Conference",
  editor =       "John R. Koza and Kalyanmoy Deb and Marco Dorigo and 
                 David B. Fogel and Max Garzon and Hitoshi Iba and 
                 Rick L. Riolo",
  year =         "1997",
  month =        "13-16 " # jul,
  keywords =     "genetic algorithms, genetic programming, SQL",
  pages =        "96--101",
  address =      "Stanford University, CA, USA",
  publisher_address = "San Francisco, CA, USA",
  publisher =    "Morgan Kaufmann",
  URL =          "http://citeseer.nj.nec.com/43454.html",
  URL =          "http://kar.kent.ac.uk/21483/",
  URL =          "http://kar.kent.ac.uk/21483/2/A_Genetic_Programming_Framework_for_Two_Data_Mining_Tasks_Classification_and_Generalized_Rule_Induction.pdf",
  size =         "6 pages",
  abstract =     "This paper proposes a genetic programming (GP)
                 framework for two major data mining tasks, namely
                 classification and generalised rule induction. The
                 framework emphasises the integration between a GP
                 algorithm and relational database systems. In
                 particular, the fitness of individuals is computed by
                 submitting SQL queries to a (parallel) database server.
                 Some advantages of this integration from a data mining
                 viewpoint are scalability, data-privacy control and
                 automatic parallelization. The paper also proposes some
                 genetic operators tailored for the two above data
                 mining tasks.",
  notes =        "GP-97

                 Lazy learning, separation of query tree encodes
                 Tuple-Set Descriptor (SQL), from goal attribute. Goal
                 subject to three types of mutation",
}

Genetic Programming entries for Alex Alves Freitas

Citations