In classifier combining, one tries to fuse the information that is given by a set of base classifiers. In such a process, one of the difficulties is how to deal with the variabilit...
Elzbieta Pekalska, Robert P. W. Duin, Marina Skuri...
This study looks at the relationships between different methods of classifier combination and different measures of diversity. We considered ten combination methods and ten measur...
Information fusion has, in the form of multiple classifier systems, long been a successful tool in pattern recognition applications. It is also becoming increasingly popular in bio...
Torsten Rohlfing, Adolf Pfefferbaum, Edith V. Sull...
In this paper, a framework for the analysis of the error-reject trade-off in linearly combined classifiers is proposed. We start from a framework developed by Tumer and Ghosh [1,2...
The use of artificial outputs generated by a classifier simulator has recently emerged as a new trend to provide an underlying evaluation of classifier combination methods. In thi...