Enhancing the Effectiveness and Interpretability of Decision Tree and Rule Induction Classifiers with Evolutionary Training Set Selection over Imbalanced Problems

Artículo de revista 2009

Salvador García López, Alberto Luis Fernández Hilario, Francisco Herrera Triguero

Applied Soft ComputingVolumen 9Páginas 1304-1314

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García López, S., Fernández Hilario, A. L., & Herrera Triguero, F. (2009). Enhancing the Effectiveness and Interpretability of Decision Tree and Rule Induction Classifiers with Evolutionary Training Set Selection over Imbalanced Problems. Applied Soft Computing, 9, 1304-1314. https://doi.org/10.1016/j.asoc.2009.04.004
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DOI
10.1016/j.asoc.2009.04.004