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

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@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