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

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