Simultaneous generation of prototypes and features through genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  author =       "Mauricio Garcia-Limon and Hugo Jair Escalante and 
                 Eduardo Morales and Alicia Morales-Reyes",
  title =        "Simultaneous generation of prototypes and features
                 through genetic programming",
  booktitle =    "GECCO '14: Proceedings of the 2014 conference on
                 Genetic and evolutionary computation",
  year =         "2014",
  editor =       "Christian Igel and Dirk V. Arnold and 
                 Christian Gagne and Elena Popovici and Anne Auger and 
                 Jaume Bacardit and Dimo Brockhoff and Stefano Cagnoni and 
                 Kalyanmoy Deb and Benjamin Doerr and James Foster and 
                 Tobias Glasmachers and Emma Hart and Malcolm I. Heywood and 
                 Hitoshi Iba and Christian Jacob and Thomas Jansen and 
                 Yaochu Jin and Marouane Kessentini and 
                 Joshua D. Knowles and William B. Langdon and Pedro Larranaga and 
                 Sean Luke and Gabriel Luque and John A. W. McCall and 
                 Marco A. {Montes de Oca} and Alison Motsinger-Reif and 
                 Yew Soon Ong and Michael Palmer and 
                 Konstantinos E. Parsopoulos and Guenther Raidl and Sebastian Risi and 
                 Guenther Ruhe and Tom Schaul and Thomas Schmickl and 
                 Bernhard Sendhoff and Kenneth O. Stanley and 
                 Thomas Stuetzle and Dirk Thierens and Julian Togelius and 
                 Carsten Witt and Christine Zarges",
  isbn13 =       "978-1-4503-2662-9",
  pages =        "517--524",
  keywords =     "genetic algorithms, genetic programming",
  month =        "12-16 " # jul,
  organisation = "SIGEVO",
  address =      "Vancouver, BC, Canada",
  URL =          "",
  DOI =          "doi:10.1145/2576768.2598356",
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  abstract =     "Nearest-neighbour (NN) methods are highly effective
                 and widely used pattern classification techniques.
                 There are, however, some issues that hinder their
                 application for large scale and noisy data sets;
                 including, its high storage requirements, its
                 sensitivity to noisy instances, and the fact that test
                 cases must be compared to all of the training
                 instances. Prototype (PG) and feature generation (FG)
                 techniques aim at alleviating these issues to some
                 extent; where, traditionally, both techniques have been
                 implemented separately. This paper introduces a genetic
                 programming approach to tackle the simultaneous
                 generation of prototypes and features to be used for
                 classification with a NN classifier. The proposed
                 method learns to combine instances and attributes to
                 produce a set of prototypes and a new feature space for
                 each class of the classification problem via genetic
                 programming. An heterogeneous representation is
                 proposed together with ad-hoc genetic operators. The
                 proposed approach overcomes some limitations of NN
                 without degradation in its classification performance.
                 Experimental results are reported and compared with
                 several other techniques. The empirical assessment
                 provides evidence of the effectiveness of the proposed
                 approach in terms of classification accuracy and
                 instance/feature reduction.",
  notes =        "Also known as \cite{2598356} GECCO-2014 A joint
                 meeting of the twenty third international conference on
                 genetic algorithms (ICGA-2014) and the nineteenth
                 annual genetic programming conference (GP-2014)",

Genetic Programming entries for Mauricio Garcia-Limon Hugo Jair Escalante Eduardo F Morales Alicia Morales-Reyes