Data Classification with Genetic Programming (Gp) -- A Case Study

Created by W.Langdon from gp-bibliography.bib Revision:1.4216

  author =       "N. Prasanna Kumari",
  title =        "Data Classification with Genetic Programming (Gp) -- A
                 Case Study",
  journal =      "International Journal of Engineering Research and
  year =         "2013",
  volume =       "7",
  number =       "4",
  pages =        "47--54",
  month =        may,
  keywords =     "genetic algorithms, genetic programming,
                 classification, data mining",
  bibsource =    "OAI-PMH server at",
  language =     "en",
  oai =          "oai:CiteSeerX.psu:",
  URL =          "",
  URL =          "",
  size =         "8 pages",
  abstract =     "Classification is one of the most researched questions
                 in data mining. A wide range of real problems have been
                 stated as classification problems, for example credit
                 scoring, bankruptcy prediction, medical diagnosis,
                 pattern recognition, text categorisation, software
                 quality assessment, and many more. The use of
                 evolutionary algorithms for training classifiers has
                 been studied in the past few decades. Genetic
                 programming is a technique to automatically discover
                 computer programs using principles of evolution.
                 Genetic operations like crossover, mutation,
                 reproduction are carried out on population to get the
                 best fitting results. In this GP is used for developing
                 a classification model for a data set and also used for
                 function generation to study its automatic code
                 generation capability.",
  notes =        "Assistant Professor, Dept of CSE AITAM Tekkali, Andhra
                 Pradesh, INDIA",

Genetic Programming entries for N Prasanna Kumari