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An Evidential Approach to Classification Combination for Text Categorisation

Bell, D., Guan, J. and Bi, Yaxin (2005) An Evidential Approach to Classification Combination for Text Categorisation. Knowledge Mining Studies in Fuzziness and Soft Computing, 185 . pp. 13-22. [Journal article]

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DOI: 10.1007/3-540-32394-5_2

Abstract

In this paper we look at a way of combining two or more different classification methods for text categorization. The specific methods we have been experimenting with in our group include the Support Vector Machine, kNN (nearest neighbours), kNN model-based approach (kNNM), and Rocchio methods. Then we describe our method for combining the classifiers. A previous study suggested that the combination of the best and the second best classifiers using evidential operations [1] can achieve better performance than other combinations. We assess some aspects of this from an evidential reasoning perspective and suggest a refinement of the approach.

Item Type:Journal article
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Mathematics
Research Institutes and Groups:Computer Science Research Institute
Computer Science Research Institute > Artificial Intelligence and Applications
ID Code:25634
Deposited By: Dr Yaxin Bi
Deposited On:18 Apr 2013 09:55
Last Modified:18 Apr 2013 09:55

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