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Character Recognition using Ensemble classifier

To improve the accuracy of data classification systems, several techniques using classifier fusion have been suggested. This paper proposed a model of classifier fusion for character recognition problem. The work presented here aims to tackle the disadvantages and benefit of different classifiers with varying feature sets. In particular, this approach proposes the use of statistical procedures for the selection of the best subgroup among different classification algorithms and the subsequent fusion of the decision of the models in this subgroup with methods like voting, weighted voting. Ensemble classifier is constructed by using Support Vector Machine and K-Nearest Neighbor. Experimental results show that the performance of proposed ensemble classifier is better as compared to other classifiers in character recognition. Keywords-Character Recognition; Ensemble classifier; Support Vector Machine; K-Nearest Neighbor.