Binary and multiclass imbalanced classification using multi-objective ant programming

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@InProceedings{Olmo:2012:isda,

• 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

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