KEEL: A software tool to assess evolutionary algorithms for Data Mining problems (regression, classification, clustering, pattern mining and so on)

KEEL-dataset - Experimental studies with Imbalanced data sets

Introduction
Experimental studies related

This section shows some relevant research papers in which some of the imbalanced data sets avalaible in KEEL-dataset have been employed.

For each study, we provide its reference (plain text and BibTeX formats), abstract and summary. A pdf version the article can also be downloaded. Additionally, we offer complementary material about the experimental studies carried up: Algorithms tested, data sets employed and results obtained (XLS and CVS formats).

Experimental studies and results with these data sets

Jump to year: 2010 (2) 2009 (1)

Year 2010 (2):

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A. Fernandez, S. García, J. Luengo, E. Bernadó-Mansilla, F. Herrera, Genetics-Based Machine Learning for Rule Induction: State of the Art, Taxonomy and Comparative Study. IEEE Transactions on Evolutionary Computation, Doi: 10.1109/TEVC.2009.2039140, In press (2010).

Link to: Data sets, algorithms and experimental results.

Link to: Website associated to this paper.

dataset/studies/imbalanced/fernandez-INS10.gif

A. Fernandez, M.J. del Jesus, F. Herrera, On the 2-Tuples Based Genetic Tuning Performance for Fuzzy Rule Based Classification Systems in Imbalanced Data-Sets. Information Sciences 180:8 (2010) 1268-1291, doi:10.1016/j.ins.2009.12.014

Link to: Data sets, algorithms and experimental results.

Year 2009 (1):

dataset/studies/imbalanced/fernandez-IJAR09.gif

A. Fernandez, M.J. del Jesus, F. Herrera, Hierarchical Fuzzy Rule Based Classification Systems with Genetic Rule Selection for Imbalanced Data-Sets. International Journal of Approximate Reasoning 50 (2009) 561-577, doi: 10.1016/j.ijar.2008.11.004

Link to: Data sets, algorithms and experimental results.