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.
- Language
-
Englisch
- Bibliographic citation
-
Series: Discussion Paper ; No. 359
- Event
-
Geistige Schöpfung
- (who)
-
Tutz, Gerhard
Hechenbichler, Klaus
- Event
-
Veröffentlichung
- (who)
-
Ludwig-Maximilians-Universität München, Sonderforschungsbereich 386 - Statistische Analyse diskreter Strukturen
- (where)
-
München
- (when)
-
2003
- DOI
-
doi:10.5282/ubm/epub.1734
- Handle
- URN
-
urn:nbn:de:bvb:19-epub-1734-2
- Last update
-
10.03.2025, 11:41 AM CET
Data provider
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Tutz, Gerhard
- Hechenbichler, Klaus
- Ludwig-Maximilians-Universität München, Sonderforschungsbereich 386 - Statistische Analyse diskreter Strukturen
Time of origin
- 2003
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