Arbeitspapier

Aggregating classifiers with ordinal response structure

In recent years the introduction of aggregation methods led to many new techniques within the field of prediction and classification. The most important developments, bagging and boosting, habe been extensively analyzed for two and multi class problems. While the proposed methods treat the class indicator as a nominal response without any structure, in many applications the class may be considered as a ordered categorical variable. In the present paper variants of bagging and boosting are proposed which make use of the ordinal structure. It is demonstrated how the predictive power is improved by use of appropriate aggregation methods. Comparisons between the methods are based on misclassification rates as well as criteria that take ordinality into account, like absolute or squared distance measures.

Sprache
Englisch

Erschienen in
Series: Discussion Paper ; No. 359

Ereignis
Geistige Schöpfung
(wer)
Tutz, Gerhard
Hechenbichler, Klaus
Ereignis
Veröffentlichung
(wer)
Ludwig-Maximilians-Universität München, Sonderforschungsbereich 386 - Statistische Analyse diskreter Strukturen
(wo)
München
(wann)
2003

DOI
doi:10.5282/ubm/epub.1734
Handle
URN
urn:nbn:de:bvb:19-epub-1734-2
Letzte Aktualisierung
10.03.2025, 11:41 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Arbeitspapier

Beteiligte

  • Tutz, Gerhard
  • Hechenbichler, Klaus
  • Ludwig-Maximilians-Universität München, Sonderforschungsbereich 386 - Statistische Analyse diskreter Strukturen

Entstanden

  • 2003

Ähnliche Objekte (12)