Method of classifier selection using the genetic approach |
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Authors: | Konrad Jackowski Michal Wozniak |
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Affiliation: | 1. Department of Systems and Computer Networks, Wroclaw University of Technology, Wybrzeze Wyspianskiego 27, 50‐370 Wroclaw, Poland Email: Michal.Wozniak@pwr.wroc.pl;2. konrad.Jackowski@pwr.wroc.pl |
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Abstract: | Abstract: The paper presents a novel machine learning algorithm used for training a compound classifier system that consists of a set of area classifiers. Area classifiers recognize objects derived from the respective competence area. Splitting feature space into areas and selecting area classifiers are two key processes of the algorithm; both take place simultaneously in the course of an optimization process aimed at maximizing the system performance. An evolutionary algorithm is used to find the optimal solution. A number of experiments have been carried out to evaluate system performance. The results prove that the proposed method outperforms each elementary classifier as well as simple voting. |
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Keywords: | pattern recognition multiple classifier system classifier selection evolutionary algorithms |
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