A Novel Genetic Programming Based Classifier Design Using a New Constructive Crossover Operator with a Local Search Technique

Created by W.Langdon from gp-bibliography.bib Revision:1.3949

@InProceedings{Bhardwaj:2013:ICIC,
  author =       "Arpit Bhardwaj and Aruna Tiwari",
  title =        "A Novel Genetic Programming Based Classifier Design
                 Using a New Constructive Crossover Operator with a
                 Local Search Technique",
  booktitle =    "International Conference on Intelligent Computing
                 (ICIC 2013)",
  year =         "2013",
  editor =       "De-Shuang Huang and Vitoantonio Bevilacqua and 
                 Juan Carlos Figueroa and Prashan Premaratne",
  volume =       "7995",
  series =       "Lecture Notes in Computer Science",
  pages =        "86--95",
  address =      "Nanning, China",
  month =        jul # " 28-31",
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming, Crossover,
                 Local Search Technique",
  isbn13 =       "978-3-642-39478-2",
  DOI =          "doi:10.1007/978-3-642-39479-9_11",
  size =         "10 pages",
  abstract =     "A common problem in genetic programming search
                 algorithms is the destructive nature of the crossover
                 operator in which the offspring of good parents
                 generally has worse performance than the parents.
                 Designing constructive crossover operators and
                 integrating some local search techniques into the
                 breeding process have been suggested as solutions. In
                 this paper, we proposed the integration of variants of
                 local search techniques in the breeding process, done
                 by allowing parents to produce many off springs and
                 applying a selection procedure to choose high
                 performing off springs. Our approach has removed the
                 randomness of crossover operator. To demonstrate our
                 approach, we designed a Multiclass classifier and
                 tested it on various benchmark datasets. Our method has
                 shown the tremendous improvement over the other state
                 of the art methods.",
}

Genetic Programming entries for Arpit Bhardwaj Aruna Tiwari

Citations