Ruta, D. and Gabrys, B., 2000. An Overview of Classifier Fusion Methods. Computing and Information Systems, 7 (1), pp. 1-10.
Full text available as:
|PDF - Published Version|
A number of classifier fusion methods have been recently developed opening an alternative approach leading to a potential improvement in the classification performance. As there is little theory of information fusion itself, currently we are faced with different methods designed for different problems and producing different results. This paper gives an overview of classifier fusion methods and attempts to identify new trends that may dominate this area of research in future. A taxonomy of fusion methods trying to bring some order into the existing “pudding of diversities” is also provided.
|Subjects:||Generalities > Computer Science and Informatics > Artificial Intelligence|
Generalities > Computer Science and Informatics
|Group:||School of Design, Engineering & Computing > Smart Technology Research Centre|
|Deposited By:||Professor Bogdan Gabrys|
|Deposited On:||11 Mar 2009 23:57|
|Last Modified:||07 Mar 2013 15:07|
Document DownloadsMore statistics for this item...
|Repository Staff Only -|
|BU Staff Only -|
|Help Guide -||Editing Your Items in BURO|