A Survey on Techniques of Improving Generalization Ability of Genetic Programming Solutions

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

@Misc{Dabhi:2012:arXiv,
  author =       "Vipul K. Dabhi and Sanjay Chaudhary",
  title =        "A Survey on Techniques of Improving Generalization
                 Ability of Genetic Programming Solutions",
  howpublished = "arXiv",
  year =         "2012",
  month =        "6 " # nov,
  keywords =     "genetic algorithms, genetic programming",
  URL =          "http://arxiv.org/abs/1211.1119",
  size =         "7 pages",
  abstract =     "In the field of empirical modelling using Genetic
                 Programming (GP), it is important to evolve solution
                 with good generalisation ability. Generalisation
                 ability of GP solutions get affected by two important
                 issues: bloat and over-fitting. We surveyed and
                 classified existing literature related to different
                 techniques used by GP research community to deal with
                 these issues. We also point out limitation of these
                 techniques, if any. Moreover, the classification of
                 different bloat control approaches and measures for
                 bloat and over-fitting are also discussed. We believe
                 that this work will be useful to GP practitioners in
                 following ways: (i) to better understand concepts of
                 generalisation in GP (ii) comparing existing bloat and
                 over-fitting control techniques and (iii) selecting
                 appropriate approach to improve generalisation ability
                 of GP evolved solutions.",
  notes =        "Information Technology Department, Dharmsinh Desai
                 University, Nadiad, INDIA.

                 DA-IICT, Gandhinagar, Gujarat, INDIA",
}

Genetic Programming entries for Vipul K Dabhi Sanjay Chaudhary

Citations