A discussion on the classifier projection space for classifier combining

EM Pekalska, RPW Duin, M Skurichina

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

14 Citations (Scopus)

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.
Original languageUndefined/Unknown
Title of host publicationMultiple Classifier Systems, Proceedings
EditorsF Roli, J Kittler
Place of PublicationBerlin
PublisherSpringer
Pages137-148
Number of pages12
ISBN (Print)3-540-43818-1
Publication statusPublished - 2002
EventThird International Workshop MCS 2002 (Cagliari, Italy) - Berlin
Duration: 24 Jun 200226 Jun 2002

Publication series

Name
PublisherSpringer Verlag
NameLecture Notes in Computer Science
Volume2364
ISSN (Print)0302-9743

Conference

ConferenceThird International Workshop MCS 2002 (Cagliari, Italy)
Period24/06/0226/06/02

Keywords

  • conference contrib. refereed
  • ZX CWTS JFIS < 1.00

Cite this

Pekalska, EM., Duin, RPW., & Skurichina, M. (2002). A discussion on the classifier projection space for classifier combining. In F. Roli, & J. Kittler (Eds.), Multiple Classifier Systems, Proceedings (pp. 137-148). (Lecture Notes in Computer Science; Vol. 2364). Springer.