Ensemble of Classifiers with Modification of Confidence Values

Abstract : In the classification task, the ensemble of classifiers have attracted more and more attention in pattern recognition communities. Generally, ensemble methods have the potential to significantly improve the prediction base classifier which are included in the team. In this paper, we propose the algorithm which modifies the confidence values. This values are obtained as an outputs of the base classifiers. The experiment results based on thirteen data sets show that the proposed method is a promising method for the development of multiple classifiers systems. We compared the proposed method with other known ensemble of classifiers and with all base classifiers.
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Communication dans un congrès
Khalid Saeed; Władysław Homenda. 15th IFIP International Conference on Computer Information Systems and Industrial Management (CISIM), Sep 2016, Vilnius, Lithuania. Springer International Publishing, Lecture Notes in Computer Science, LNCS-9842, pp.473-480, 2016, Computer Information Systems and Industrial Management. 〈10.1007/978-3-319-45378-1_42〉
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Robert Burduk, Paulina Baczyńska. Ensemble of Classifiers with Modification of Confidence Values. Khalid Saeed; Władysław Homenda. 15th IFIP International Conference on Computer Information Systems and Industrial Management (CISIM), Sep 2016, Vilnius, Lithuania. Springer International Publishing, Lecture Notes in Computer Science, LNCS-9842, pp.473-480, 2016, Computer Information Systems and Industrial Management. 〈10.1007/978-3-319-45378-1_42〉. 〈hal-01637486〉

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