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Classifier learning with data-sets that suffer from imbalanced class distributions is a challenging problem in data mining community. This issue occurs when the number of examples that represent one class is much lower than the ones of the other classes. Its presence in many real-world applications has brought along a growth of attention from researchers. In machine learning, the ensemble of classifiers...
Fuzzy decision trees are widely employed to face classification problems since they combine the high interpretability given by the decision tree and the capability of management of the uncertainty inherent to fuzzy logic. However, the success of fuzzy systems in general depends, to a large degree, on the choice of the membership functions. For this reason, we propose to model the linguistic labels...
In this work we propose an image reduction algorithm based on weak local reduction operators. We use several averaging functions to build these operators and we analyze their properties. We present experimental results where we apply the algorithm and weak local reduction operators in procedures of reduction, and later, reconstruction of images. We analyze these results over natural images and noisy...
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