An evolutionary cluster validation index

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

@InProceedings{Oh:2008:BICTA,
  author =       "Sanghoun Oh and Chang Wook Ahn and Moongu Jeon",
  title =        "An evolutionary cluster validation index",
  booktitle =    "3rd International Conference on Bio-Inspired
                 Computing: Theories and Applications, BICTA 2008",
  year =         "2008",
  month =        "28 " # sep # "-1 " # oct,
  pages =        "83--88",
  keywords =     "genetic algorithms, genetic programming, evolutionary
                 cluster validation index, fitness function, random
                 factors, training data set, pattern clustering",
  DOI =          "doi:10.1109/BICTA.2008.4656708",
  abstract =     "This paper presents a new evolutionary method for the
                 cluster validation index (CVI), namely eCVI. The
                 proposed method learns CVI from the generated training
                 data set using the genetic programming (GP), and then
                 outputs the optimal number of clusters after taking
                 parameters of a test data set into the learned CVI.
                 Each chromosome encodes a possible CVI as a function of
                 the number of clusters, density measure of clusters,
                 and some random factors. Fitness function evaluating
                 each candidate is defined by the difference between the
                 actual number of clusters from training data set and
                 the number of clusters computed by the current CVI.
                 Because of the adaptive nature of GP, the proposed eCVI
                 is reliable and robust in various types of data sets.
                 Experimental results provide grounds for the dominance
                 of eCVI over several widely-known CVIs.",
  notes =        "Also known as \cite{4656708}",
}

Genetic Programming entries for Sanghoun Oh Chang Wook Ahn Moongu Jeon

Citations