Arbeitspapier
On a strategy to develop robust and simple tariffs from motor vehicle insurance data
The goals of this paper are twofold: we describe common features in data sets from motor vehicle insurance companies and we investigate a general strategy which exploits the knowledge of such features. The results of the strategy are a basis to develop insurance tariffs. The strategy is applied to a data set from motor vehicle insurance companies. We use a nonparametric approach based on a combination of kernel logistic regression and ¡support vector regression.
- Language
-
Englisch
- Bibliographic citation
-
Series: Technical Report ; No. 2004,16
- Subject
-
Classification
Data Mining
Insurance tariffs
Kernel logistic regression
Machine learning
Regression
Robustness
Simplicity
Support Vector Machine
Support Vector Regression
Kraftfahrtversicherung
Versicherungsprämie
Regression
Theorie
Data Mining
- Event
-
Geistige Schöpfung
- (who)
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Christmann, Andreas
- Event
-
Veröffentlichung
- (who)
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Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen
- (where)
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Dortmund
- (when)
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2004
- Handle
- Last update
-
10.03.2025, 11:42 AM CET
Data provider
This object is provided by:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the 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
- Christmann, Andreas
- Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen
Time of origin
- 2004
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