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We present a methodology for the automatic construction of multi-classifiers systems based on the combination of selection and fusion. The proposed methodology initially finds the optimum number of clusters for training data set and subsequently determines an ensemble for each cluster found. Self-organizing maps were used in the clustering phase, and multilayer perceptrons, in the classification phase...
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