A multiclass classifier using Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4208

  author =       "Narendra S. Chaudhari and Anuradha Purohit and 
                 Aruna Tiwari",
  title =        "A multiclass classifier using Genetic Programming",
  booktitle =    "10th International Conference on Control, Automation,
                 Robotics and Vision, ICARCV 2008",
  year =         "2008",
  pages =        "1884--1887",
  address =      "Hanoi, Vietnam",
  month =        "17-20 " # dec,
  publisher =    "IEEE",
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1109/ICARCV.2008.4795815",
  abstract =     "his paper presents an approach for designing
                 classifiers for a multiclass problem using Genetic
                 Programming (GP). The proposed approach takes an
                 integrated view of all classes when GP evolves. An
                 individual of the population will be represented using
                 multiple trees. The GP is trained with a set of N
                 training samples in steps. A concept of unfitness of a
                 tree is used in order to improve genetic evolution.
                 Weak trees having poor performance are given more
                 chance to participate in the genetic operations, and
                 thus improve themselves. In this context, a new
                 mutation operation called nondestructive directed point
                 mutation is used, which reduces the destructive nature
                 of mutation operation. The approach is being
                 demonstrated by experimenting on some datasets.",
  bibsource =    "DBLP, http://dblp.uni-trier.de",

Genetic Programming entries for Narendra S Chaudhari Anuradha Purohit Aruna Tiwari