Husin, Abdullah (2019) DESIGNING MULTIPLE CLASSIFIER COMBINATIONS A SURVEY. Journal of Theoretical and Applied Information Technology, 97 (20). pp. 2386-2405. ISSN 1992-8645

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Classification accuracy can be improved through multiple classifier approach. It has been proven that multiple classifier combinations can successfully obtain better classification accuracy than using a single classifier. There are two main problems in designing a multiple classifier combination which are determining the classifier ensemble and combiner construction. This paper reviews approaches in constructing the classifier ensemble and combiner. For each approach, methods have been reviewed and 2 their advantages and disadvantages have been highlighted. A random strategy and majority voting are the most commonly used to construct the ensemble and combiner, respectively. The results presented in this review are expected to be a roadmap in designing multiple classifier combinations.

Item Type: Article
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science
Depositing User: Dr Abdullah Husin
Date Deposited: 18 Aug 2020 00:00
Last Modified: 18 Aug 2020 00:00

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