Evolutionary Approach for Automated Discovery of Censored Production Rules

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

@Article{Bharadwaj:2007:waset,
  author =       "Kamal K. Bharadwaj and Basheer M. Al-Maqaleh",
  title =        "Evolutionary Approach for Automated Discovery of
                 Censored Production Rules",
  journal =      "International Journal of Computer, Information Science
                 and Engineering",
  volume =       "1",
  number =       "10",
  year =         "2007",
  pages =        "11--16",
  keywords =     "genetic algorithms, genetic programming, data mining,
                 machine learning, evolutionary algorithms",
  bibsource =    "http://waset.org/Publications",
  ISSN =         "1307-6892",
  publisher =    "World Academy of Science, Engineering and Technology",
  index =        "International Science Index 10, 2007",
  language =     "en",
  oai =          "oai:CiteSeerX.psu:10.1.1.308.7101",
  URL =          "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.308.7101",
  URL =          "http://waset.org/publications/14169",
  URL =          "http://waset.org/Publications?p=10",
  size =         "6 pages",
  abstract =     "In the recent past, there has been an increasing
                 interest in applying evolutionary methods to Knowledge
                 Discovery in Databases (KDD) and a number of successful
                 applications of Genetic Algorithms (GA) and Genetic
                 Programming (GP) to KDD have been demonstrated. The
                 most predominant representation of the discovered
                 knowledge is the standard Production Rules (PRs) in the
                 form If P Then D. The PRs, however, are unable to
                 handle exceptions and do not exhibit variable
                 precision. The Censored Production Rules (CPRs), an
                 extension of PRs, were proposed by Michalski & Winston
                 that exhibit variable precision and supports an
                 efficient mechanism for handling exceptions. A CPR is
                 an augmented production rule of the form:

                 If P Then D Unless C, where C (Censor) is an exception
                 to the rule. Such rules are employed in situations, in
                 which the conditional statement 'If P Then D' holds
                 frequently and the assertion C holds rarely. By using a
                 rule of this type we are free to ignore the exception
                 conditions, when the resources needed to establish its
                 presence are tight or there is simply no information
                 available as to whether it holds or not. Thus, the 'If
                 P Then D' part of the CPR expresses important
                 information, while the Unless C part acts only as a
                 switch and changes the polarity of D to ~D. This paper
                 presents a classification algorithm based on
                 evolutionary approach that discovers comprehensible
                 rules with exceptions in the form of CPRs.

                 The proposed approach has flexible chromosome encoding,
                 where each chromosome corresponds to a CPR. Appropriate
                 genetic operators are suggested and a fitness function
                 is proposed that incorporates the basic constraints on
                 CPRs. Experimental results are presented to demonstrate
                 the performance of the proposed algorithm.",
  notes =        "oai:CiteSeerX.psu:10.1.1.308.7101
                 http://waset.org/publications/14169",
}

Genetic Programming entries for K K Bharadwaj Basheer Mohamad Ahmad Al-Maqaleh

Citations