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Statistical and Heuristic Model Selection in Regularized Least-Squares.

, and . BRACIS, page 231-236. IEEE Computer Society, (2013)

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Prolog & TXL: Um Estudo de Caso para Prototipação de Ferramentas de Apoio para o Teste Estrutural., , , and . JIISIC, page 15-22. Editorial Universidad Nacional de Jujuy, San Salvador de Jujuy, Argentina, (2001)Splice Junction Recognition using Machine Learning Techniques., , , and . WOB, page 32-39. (2002)On the estimation of the number of fuzzy sets for fuzzy rule-based classification systems., , , and . HIS, page 211-216. IEEE, (2011)Learning with Class Skews and Small Disjuncts., , and . SBIA, volume 3171 of Lecture Notes in Computer Science, page 296-306. Springer, (2004)Data mining with imbalanced class distributions: concepts and methods., , and . IICAI, page 359-376. IICAI, (2009)Evolving Sets of Symbolic Classifiers into a Single Symbolic Classifier Using Genetic Algorithms., , and . HIS, page 525-530. IEEE Computer Society, (2008)Improving the kernel regularized least squares method for small-sample regression., and . Neurocomputing, (2015)Applying Genetic and Symbolic Learning Algorithms to Extract Rules from Artificial Neural Networks., , , and . MICAI, volume 2972 of Lecture Notes in Computer Science, page 833-843. Springer, (2004)Constructing Ensembles of Symbolic Classifiers., , and . HIS, page 315-322. IEEE Computer Society, (2005)The Influence of Noisy Patterns in the Performance of Learning Methods in the Splice Junction Recognition Problem., , , and . SBRN, page 31-37. IEEE Computer Society, (2002)