A preliminary study on overlapping and data fracture in imbalanced domains by means of Genetic Programming-based feature extraction

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@InProceedings{Moreno-Torres:2010:ISDA,
  author =       "Jose G. Moreno-Torres and Francisco Herrera",
  title =        "A preliminary study on overlapping and data fracture
                 in imbalanced domains by means of Genetic
                 Programming-based feature extraction",
  booktitle =    "10th International Conference on Intelligent Systems
                 Design and Applications (ISDA)",
  year =         "2010",
  month =        nov # " 29-" # dec # " 1",
  pages =        "501--506",
  keywords =     "genetic algorithms, genetic programming, bidimensional
                 graph, data fracture, data mining, genetic
                 programming-based feature extraction, imbalanced data
                 classification, rough set theory, data mining, feature
                 extraction, pattern classification, rough set theory",
  DOI =          "doi:10.1109/ISDA.2010.5687214",
  size =         "6 pages",
  abstract =     "The classification of imbalanced data is a
                 well-studied topic in data mining. However, there is
                 still a lack of understanding of the factors that make
                 the problem difficult. In this work, we study the two
                 main reasons that make the classification of imbalanced
                 datasets complex: overlapping and data fracture. We
                 present a Genetic Programming-based feature extraction
                 method driven by Rough Set Theory to help visualize the
                 data in a bidimensional graph, to better understand how
                 the presence of overlapping and data fractures affect
                 classification performance.",
  notes =        "Also known as \cite{5687214}",
}

Genetic Programming entries for Jose Garcia Moreno-Torres Francisco Herrera

Citations