André Ribeiro

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In this work a Multi-Objective Evolutionary Algorithm (MOEA) was applied for feature selection in the problem of bankruptcy prediction. This algorithm maximizes the accuracy of the classifier while keeping the number of features low. A two-objective problem, that is minimization of the number of features and accuracy maximization, was fully analyzed using(More)
Nowadays, mobile applications are becoming increasingly more present in our daily life, allowing people to perform several tasks through the use of smartphones, tablets or equivalent devices. Despite the great benefits in terms of innovation and in the variety of available solutions, the rapid and continuous growth of the mobile market has resulted in some(More)
Network theory methods are being increasingly applied to proteins to investigate complex biological phenomena. Residues that are important for signaling processes can be identified by their condition as critical nodes in a protein structure network. This analysis involves modeling the protein as a graph in which each residue is represented as a node and(More)
A Multi-Objective Evolutionary Algorithm (MOEA) was adapted in order to deal with problems of feature selection in data-mining. The aim is to maximize the accuracy of the classifier and/or to minimize the errors produced while minimizing the number of features necessary. A Support Vector Machines (SVM) classifier was adopted. Simultaneously, the parameters(More)
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