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Reported results using the datasets in this repository

  1. Coordination number prediction using Learning Classifier Systems: Performance and interpretability
    J. Bacardit, M. Stout, J.D. Hirst, N. Krasnogor and J. Blazewicz
    In Proceedings of the 8th Annual Conference on Genetic and Evolutionary Computation (GECCO2006), pp. 247-254, ACM Press, 2006
    gecco2006-cn.pdf

    Naive Bayes, C4.5 and LIBSVM and the GAssist learning classifier system were evaluated using the classification version of this dataset with the AA representation, window size of 4, using 2, 3 and 5 classes and discretization methods

  2. Fast Rule Representation for Continuous Attributes in Genetics-Based Machine Learning
    Bacardit, J. and Krasnogor, N.
    In Proceedings of the 10th Annual Conference on Genetic and Evolutionary Computation (GECCO2008), to appear, ACM Press, 2008
    gecco2008.pdf

    The BioHEL evolutionary learning system was evaluated on the classification verion of the dataset using the PSSM representation, window size of 4, 2 classes and uneven class distribution.