Discovering Subgroups by Means of Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{luna:2013:EuroGP,
  author =       "Jose M. Luna and Jose R. Romero and 
                 Cristobal Romero and Sebastian Ventura",
  title =        "Discovering Subgroups by Means of Genetic
                 Programming",
  booktitle =    "Proceedings of the 16th European Conference on Genetic
                 Programming, EuroGP 2013",
  year =         "2013",
  month =        "3-5 " # apr,
  editor =       "Krzysztof Krawiec and Alberto Moraglio and Ting Hu and 
                 A. Sima Uyar and Bin Hu",
  series =       "LNCS",
  volume =       "7831",
  publisher =    "Springer Verlag",
  address =      "Vienna, Austria",
  pages =        "121--132",
  organisation = "EvoStar",
  keywords =     "genetic algorithms, genetic programming, grammar
                 guided genetic programming, Data mining, subgroup
                 discovery",
  isbn13 =       "978-3-642-37206-3",
  DOI =          "doi:10.1007/978-3-642-37207-0_11",
  abstract =     "This paper deals with the problem of discovering
                 subgroups in data by means of a grammar guided genetic
                 programming algorithm, each subgroup including a set of
                 related patterns. The proposed algorithm combines the
                 requirements of discovering comprehensible rules with
                 the ability of mining expressive and flexible solutions
                 thanks to the use of a context-free grammar. A major
                 characteristic of this algorithm is the small number of
                 parameters required, so the mining process is easy for
                 end-users.

                 The algorithm proposed is compared with existing
                 subgroup discovery evolutionary algorithms. The
                 experimental results reveal the excellent behaviour of
                 this algorithm, discovering comprehensible subgroups
                 and behaving better than the other algorithms. The
                 conclusions obtained were reinforced through a series
                 of non-parametric tests.",
  notes =        "Part of \cite{Krawiec:2013:GP} EuroGP'2013 held in
                 conjunction with EvoCOP2013, EvoBIO2013, EvoMusArt2013
                 and EvoApplications2013",
}

Genetic Programming entries for Jose Maria Luna Jose Raul Romero Salguero Cristobal Romero Morales Sebastian Ventura

Citations