An Improved Knowledge-Acquisition Strategy Based on Genetic Programming

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

@Article{journals/cas/KuoHC08,
  title =        "An Improved Knowledge-Acquisition Strategy Based on
                 Genetic Programming",
  author =       "Chan-Sheng Kuo and Tzung-Pei Hong and 
                 Chuen-Lung Chen",
  journal =      "Cybernetics and Systems",
  year =         "2008",
  number =       "7",
  volume =       "39",
  bibdate =      "2008-12-12",
  bibsource =    "DBLP,
                 http://dblp.uni-trier.de/db/journals/cas/cas39.html#KuoHC08",
  pages =        "672--685",
  DOI =          "doi:10.1080/01969720802257881",
  month =        oct,
  keywords =     "genetic algorithms, genetic programming",
  size =         "15 pages",
  abstract =     "Knowledge acquisition can deal with the task of
                 extracting desirable or useful knowledge from data sets
                 for a practical application. In this paper, we have
                 modified our previous gp-based learning strategy to
                 search for an appropriate classification tree. The
                 proposed approach consists of three phases: knowledge
                 creation, knowledge evolution, and knowledge output. In
                 the creation phase, a set of classification trees are
                 randomly generated to form an initial knowledge
                 population. In the evolution phase, the genetic
                 programming technique is used to generate a good
                 classification tree. In the output phase, the final
                 derived classification tree is transferred as a rule
                 set, then outputted to the knowledge base to facilitate
                 the inference of new data. One new genetic operator,
                 separation, is designed in this proposed approach to
                 remove contradiction, thus producing more accurate
                 classification rules. Experimental results from the
                 diagnosis of breast cancers also show the feasibility
                 of the proposed algorithm.",
}

Genetic Programming entries for Chan-Sheng Kuo Tzung-Pei Hong Samuel Chuen-Lung Chen

Citations