Binary and multiclass imbalanced classification using multi-objective ant programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4524

  author =       "Juan Luis Olmo and Alberto Cano and 
                 Jose Raul Romero and Sebastian Ventura",
  booktitle =    "12th International Conference on Intelligent Systems
                 Design and Applications (ISDA 2012)",
  title =        "Binary and multiclass imbalanced classification using
                 multi-objective ant programming",
  year =         "2012",
  pages =        "70--76",
  keywords =     "genetic algorithms, genetic programming, ACO",
  DOI =          "doi:10.1109/ISDA.2012.6416515",
  size =         "7 pages",
  abstract =     "Classification in imbalanced domains is a challenging
                 task, since most of its real domain applications
                 present skewed distributions of data. However, there
                 are still some open issues in this kind of problem.
                 This paper presents a multi-objective grammar-based ant
                 programming algorithm for imbalanced classification,
                 capable of addressing this task from both the binary
                 and multiclass sides, unlike most of the solutions
                 presented so far. We carry out two experimental studies
                 comparing our algorithm against binary and multiclass
                 solutions, demonstrating that it achieves an excellent
                 performance for both binary and multiclass imbalanced
                 data sets.",
  notes =        "Also known as \cite{6416515}",

Genetic Programming entries for Juan Luis Olmo Alberto Cano Rojas Jose Raul Romero Salguero Sebastian Ventura