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Titlebook: Advances in Artificial Intelligence; 14th Conference of t Jose A. Lozano,José A. Gámez,José A. Moreno Conference proceedings 2011 Springer-

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Carsten Drebenstedt,Mahmut Kuyumcud successfully in classification problems. This paper studies their performance for imbalanced problems. These trees give better results that standard decision trees (J48, based on C4.5) and decision trees specific for imbalanced data (CCPDT: Class Confidence Proportion Decision Trees). Moreover, di
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,Nachnutzung und Flächenvermarktung,ions. One of the ways of scaling up the .-nearest neighbors classifier to deal with huge datasets is instance selection. Due to the constantly growing amount of data in almost any pattern recognition task, we need more efficient instance selection algorithms, which must achieve larger reductions whi
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https://doi.org/10.1007/978-3-642-51831-7he techniques for processing such data, which cannot be properly managed by classical statistics. The von Mises distribution is the best known angular distribution. We extend the naive Bayes classifier to the case where directional predictive variables are modeled using von Mises distributions. We f
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