Automatic Selection Of Features For Classification Using Genetic Programming

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

  author =       "J. Sherrah and R. Bogner and B. Bouzerdoum",
  title =        "Automatic Selection Of Features For Classification
                 Using Genetic Programming",
  booktitle =    "Proceedings of the 1996 Australian and New Zealand
                 Conference on Intelligent Information Systems",
  year =         "1996",
  pages =        "284--287",
  address =      "Adelaide, SA, Australia",
  month =        "18.-20 " # nov,
  publisher =    "IEEE",
  keywords =     "genetic algorithms, genetic programming",
  URL =          "",
  URL =          "",
  annote =       "The Pennsylvania State University CiteSeer Archives",
  language =     "en",
  oai =          "oai:CiteSeerPSU:263920",
  rights =       "unrestricted",
  URL =          "",
  abstract =     "Classifier design often involves the hand-selection of
                 features, a process which relies on human experience
                 and heuristics. We present the Evolutionary
                 Pre-processor, a system which automatically extracts
                 features for a range of classification problems. The
                 Evolutionary Pre-processor uses genetic programming to
                 allow useful features to emerge from the data,
                 simulating the innovative work of the human designer.
                 The Evolutionary Pre-processor improved the
                 classification performance of a linear machine on two
                 real-world problems. Although these problems are
                 intuitively difficult to solve, the Evolutionary
                 Pre-processor was able to generate complex feature
                 sets. The classification results are comparable with
                 those achieved by other classifiers",

Genetic Programming entries for Jamie R Sherrah Robert E Bogner B Bouzerdoum