The Assessment and Application of Lineage Information in Genetic Programs for Producing Better Models

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@InProceedings{Boetticher:2006:IRI,
  author =       "G. D. Boetticher and K. Kaminsky",
  title =        "The Assessment and Application of Lineage Information
                 in Genetic Programs for Producing Better Models",
  booktitle =    "IEEE International Conference on Information Reuse and
                 Integration",
  year =         "2006",
  pages =        "141--146",
  address =      "Waikoloa Village, HI, USA",
  month =        sep,
  publisher =    "IEEE",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "0-7803-9788-6",
  DOI =          "doi:10.1109/IRI.2006.252403",
  abstract =     "One of the challenges in data mining, and in
                 particular genetic programs, is to provide sufficient
                 coverage of the search space in order to produce an
                 acceptable model. Traditionally, genetic programs
                 generate equations (chromosomes) and consider all
                 chromosomes within a population for breeding purposes.
                 Considering the enormity of the search space for
                 complex problems, it is imperative to examine genetic
                 programs breeding efforts in order to produce better
                 solutions with less training. This research examines
                 chromosome lineage within genetic programs in order to
                 identify breeding patterns. Fitness values for
                 chromosomes are sorted, then partitioned into five
                 classes. Initial experiments reveal a distinct
                 difference between upper, middle, and lower classes.
                 Based upon initial results, a novel genetic programming
                 process is proposed which breeds a new generation
                 exclusively from the top 20 percent of a population. A
                 second set of experiments statistically validate this
                 proposed approach",
  notes =        "Houston Univ., TX",
}

Genetic Programming entries for Gary D Boetticher Kim Kaminsky

Citations