A discussion on the classifier projection space for classifier combining

Conference paper (2002)

Authors

E.M. Pekalska ImPhys/Quantitative Imaging
Bob Duin ImPhys/Quantitative Imaging
M Skurichina ImPhys/Quantitative Imaging
Research Group
ImPhys/Quantitative Imaging
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Published Date

2002

Language

Undefined/Unknown

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Research Group

ImPhys/Quantitative Imaging

Abstract

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 variability between classifiers. Although various measures and many combining rules have been suggested in the past, the problem of constructing optimal combiners is still heavily studied.
In this paper, we discuss and illustrate the possibilities of classifier embedding in order to analyse the variability of base classifiers, as well as their combining rules. Thereby, a space is constructed in which classifiers can be represented as points. Such a space of a low dimensionality is a Classifier Projection Space (CPS). In the first instance, it is used to design a visual tool that gives more insight into the differences of various combining techniques. This is illustrated by some examples. In the end, we discuss how the CPS may also be used as a basis for constructing new combining rules.