Experiments on Brood Size in GP with Brood Recombination Crossover for Object Recognition

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

@TechReport{vuw-CS-TR-06-6,
  author =       "Mengjie Zhang and Xiaoying Gao and Minh Duc Cao",
  title =        "Experiments on Brood Size in GP with Brood
                 Recombination Crossover for Object Recognition",
  institution =  "Computer Science, Victoria University of Wellington",
  year =         "2006",
  number =       "CS-TR-06-6",
  address =      "New Zealand",
  keywords =     "genetic algorithms, genetic programming, Document
                 Classification, Baysian Networks, Citation Links",
  URL =          "http://www.mcs.vuw.ac.nz/comp/Publications/CS-TR-06-6.abs.html",
  URL =          "http://www.mcs.vuw.ac.nz/comp/Publications/archive/CS-TR-06/CS-TR-06-6.pdf",
  abstract =     "citation links to improve the scientific paper
                 classification performance. In this approach, we
                 develop two refinement functions, a linear label
                 refinement (LLR) and a probabilistic label refinement
                 (PLR), to model the citation link structures of the
                 scientific papers for refining the class labels of the
                 documents obtained by the content-based Naive Bayes
                 classification method. The approach with the two new
                 refinement models is examined and compared with the
                 content-based Naive Bayes method on a standard paper
                 classification data set with increasing training set
                 sizes. The results suggest that both refinement models
                 can significantly improve the system performance over
                 the content-based method for all the training set sizes
                 and that PLR is better than LLR when the training
                 examples are sufficient.",
}

Genetic Programming entries for Mengjie Zhang Xiaoying (Sharon) Gao Minh Duc Cao

Citations