Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/49326
Authors: 
Christmann, Andreas
Year of Publication: 
2004
Series/Report no.: 
Technical Report // Universität Dortmund, SFB 475 Komplexitätsreduktion in Multivariaten Datenstrukturen 2004,16
Abstract: 
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.
Subjects: 
Classification
Data Mining
Insurance tariffs
Kernel logistic regression
Machine learning
Regression
Robustness
Simplicity
Support Vector Machine
Support Vector Regression
Document Type: 
Working Paper

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