Single classifier based multiple classifications

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Single classifier based multiple classifications

Ko, Albert Hung Ren and Sabourin, Robert

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2013

Abstract : In this paper, a Single Classifier-based Multiple Classification Scheme (SMCS) is proposed as an alternative multiple classification scheme. The SMCS uses only a single classifier to generate multiple classifications for a given test data point. Because of the presence of multiple classifications, classification combination schemes, such as majority voting, can be applied, and so the mechanism may improve the recognition rate in a manner similar to that of Multiple Classifier Systems (MCS). The experimental results confirmthe validity of the proposed SMCS as applicable to many classification systems. © Springer-Verlag 2013.

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