Adriana da Costa F. Chaves

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This paper proposes a fuzzy rule extraction method from support vector machines. Support vector machines (SVM) are learning systems based on statistical learning theory that have been successfully applied to a wide variety of application. However, SVM are "black box" models, that is, they generate a solution with linear combination of kernel functions which(More)
This paper proposes a new method for fuzzy rule extraction from trained support vector machines (SVMs) for multi-class problems, named FREx_SVM. SVMs have been used in a variety of applications. However, they are considered “black box models,” where no interpretation about the input–output mapping is provided. Some methods to reduce this limitation have(More)
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