Genetic Programming Based Data Projections for Classification Tasks

Created by W.Langdon from gp-bibliography.bib Revision:1.4340

  title =        "Genetic Programming Based Data Projections for
                 Classification Tasks",
  author =       "Cesar Estebanez and Ricardo Aler and 
                 Jose Maria Valls",
  year =         "2005",
  pages =        "56--61",
  editor =       "Cemal Ardil",
  publisher =    "Enformatika, \c{C}anakkale, Turkey",
  booktitle =    "International Enformatika Conference, IEC'05",
  volume =       "7",
  address =      "Prague, Czech Republic",
  month =        aug # " 26-28",
  organisation = "World Enformatika Society",
  note =         "CDROM",
  bibdate =      "2005-10-13",
  bibsource =    "DBLP,
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "975-98458-6-5",
  URL =          "",
  URL =          "",
  size =         "6 pages",
  abstract =     "In this paper we present a GP-based method for
                 automatically evolve projections, so that data can be
                 more easily classified in the projected spaces. At the
                 same time, our approach can reduce dimensionality by
                 constructing more relevant attributes. Fitness of each
                 projection measures how easy is to classify the dataset
                 after applying the projection. This is quickly computed
                 by a Simple Linear Perceptron. We have tested our
                 approach in three domains. The experiments show that it
                 obtains good results, compared to other Machine
                 Learning approaches, while reducing dimensionality in
                 many cases",

Genetic Programming entries for Cesar Estebanez Ricardo Aler Mur Jose Maria Valls Ferran