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)


    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
    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

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


    ConferenceThird International Workshop MCS 2002 (Cagliari, Italy)


    • conference contrib. refereed
    • ZX CWTS JFIS < 1.00

    Cite this