Application of a Genetic Programming Based Rule Discovery System to Recurring Miscarriage Data

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{Setzkorn:2000:AGP,
  author =       "Christian Setzkorn and Ray C. Paton and 
                 Leanne Bricker and Roy G. Farquharson",
  title =        "Application of a Genetic Programming Based Rule
                 Discovery System to Recurring Miscarriage Data",
  volume =       "1933",
  pages =        "250--259",
  year =         "2000",
  booktitle =    "Medical Data Analysis: First International Symposium,
                 ISMDA 2000, Proceedings",
  editor =       "R. W. Brause and E. Hanisch",
  series =       "Lecture Notes in Computer Science",
  address =      "Frankfurt, Germany",
  publisher_address = "Heidelberg",
  month =        sep # " 29-30",
  publisher =    "Springer-Verlag",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "3-540-41089-9",
  CODEN =        "LNCSD9",
  ISSN =         "0302-9743",
  bibdate =      "Tue Sep 10 19:08:54 MDT 2002",
  acknowledgement = ack-nhfb,
  DOI =          "doi:10.1007/3-540-39949-6_31",
  size =         "10 pages",
  abstract =     "This paper introduces a rule inference system based on
                 the paradigm of genetic programming. Rules are deduced
                 from a medical data set related to recurring
                 miscarriage. A rule consists of an IF-part (antecedent)
                 and a THEN-part (consequent). The system has to be
                 supplied with the consequent and works out antecedents.
                 An antecedent classifies the predictive class which is
                 represented by the supplied consequent. The antecedents
                 produced take the form of a tree, where Boolean
                 operations such as AND, OR and NOT represent nodes, and
                 Boolean expressions represent the leaves. Boolean
                 expressions can be built from nominal and numeric
                 attribute values, which makes the system very
                 versatile.",
}

Genetic Programming entries for Christian Setzkorn Ray C Paton Leanne Bricker Roy G Farquharson

Citations