Construction of classifier with feature selection based on genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4221

  author =       "Anuradha Purohit and Narendra S. Chaudhari and 
                 Aruna Tiwari",
  title =        "Construction of classifier with feature selection
                 based on genetic programming",
  booktitle =    "IEEE Congress on Evolutionary Computation (CEC 2010)",
  year =         "2010",
  address =      "Barcelona, Spain",
  month =        "18-23 " # jul,
  publisher =    "IEEE Press",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-1-4244-6910-9",
  abstract =     "This paper presents a genetic programming (GP) based
                 approach for designing classifiers with feature
                 selection using a modified crossover operator [12]. The
                 proposed GP methodology simultaneously selects a good
                 subset of features and constructs a classifier using
                 the selected features. For a c-class problem, it
                 provides a classifier having c trees. To overcome the
                 difficulties with standard crossover operator, we have
                 used a crossover operator which discovers the best
                 possible crossover site for a subtree and attains
                 higher fitness values while processing fewer
                 individuals. We have tested our method on several
                 datasets having large number of features. We have
                 compared the performance of our method with results
                 available in the literature and found that the proposed
                 method generates good results.",
  DOI =          "doi:10.1109/CEC.2010.5586536",
  notes =        "WCCI 2010. Also known as \cite{5586536}",

Genetic Programming entries for Anuradha Purohit Narendra S Chaudhari Aruna Tiwari