Feature Selection Using Geometric Semantic Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4192

  author =       "G. H. Rosa and J. P. Papa and L. P. Papa",
  title =        "Feature Selection Using Geometric Semantic Genetic
  booktitle =    "Proceedings of the Genetic and Evolutionary
                 Computation Conference Companion",
  series =       "GECCO '17",
  year =         "2017",
  isbn13 =       "978-1-4503-4939-0",
  address =      "Berlin, Germany",
  pages =        "253--254",
  size =         "2 pages",
  URL =          "http://doi.acm.org/10.1145/3067695.3076020",
  DOI =          "doi:10.1145/3067695.3076020",
  acmid =        "3076020",
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  keywords =     "genetic algorithms, genetic programming, feature
                 selection, geometric semantic genetic programming",
  month =        "15-19 " # jul,
  abstract =     "Feature selection concerns the task of finding the
                 subset of features that are most relevant to some
                 specific problem in the context of machine learning.
                 During the last years, the problem of feature selection
                 has been modelled as an optimization task, where the
                 idea is to find the subset of features that maximize
                 some fitness function, which can be a given
                 classifier's accuracy or even some measure concerning
                 the samples separability in the feature space, for
                 instance. In this paper, we introduced Geometric
                 Semantic Genetic Programming (GSGP) in the context of
                 feature selection, and we experimentally showed it can
                 work properly with both conic and non-conic fitness
  notes =        "Also known as \cite{Rosa:2017:FSU:3067695.3076020}
                 GECCO-2017 A Recombination of the 26th International
                 Conference on Genetic Algorithms (ICGA-2017) and the
                 22nd Annual Genetic Programming Conference (GP-2017)",

Genetic Programming entries for Gustavo Rosa Joao Paulo Papa Luciene Patrici Papa