Diogo F. de Oliveira

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The use of intelligent agents in the structure of multiclassifier systems has been investigated in order to overcome some drawbacks of these systems and, as a consequence, to improve the performance of such systems. As a result of this, the NeurAge system was proposed. This system has presented good results in some centralized and distributed classification(More)
Feature selection methods are applied in ensembles in order to find subsets of features for the classifiers of the ensemble. The use of these methods aims to reduce the redundancy of the features as well as to increase diversity of the classifiers of an ensemble. In this paper, a comparative analysis of six different feature selection methods is performed(More)
Classifier ensembles, also known as committees, are systems composed of a set of base classifiers (organized in a parallel way) and a combination module, which is responsible for providing the final output of the system. The main aim of using ensembles is to provide better performance than the individual classifiers. In order to build robust ensembles, it(More)
The ClassAge system is a multi-agent system for classification tasks. This system was proposed as an attempt to include the idea of intelligent agents in the structure of multi-classifier systems (MCSs). Also, it is aimed to overcome some drawbacks of MCSs and, as a consequence, to improve the performance of such systems. In this paper, an extension of(More)
The idea of including intelligent agents in the structure of multi-classifier systems has emerged in order to overcome some drawbacks of these systems and, as a consequence, to improve the performance of such systems. As a result of this, the ClassAge system was proposed. This system has presented good results in some classification tasks. In this paper, an(More)
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