Authors: Christmann, Andreas
Title: On a Strategy to Develop Robust and Simple Tariffs from Motor Vehicle Insurance Data
Language (ISO): en
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 e-support vector regression.
Subject Headings: data mining
insurance tariffs
kernel logistic regression
machine learning
regression
robustness
simplicity
support vector machine
support vector regression
URI: http://hdl.handle.net/2003/4872
http://dx.doi.org/10.17877/DE290R-15069
Issue Date: 2004
Publisher: Universitätsbibliothek Dortmund
Appears in Collections:Sonderforschungsbereich (SFB) 475

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