| On a Strategy to Develop Robust and Simple Tariffs from Motor Vehicle Insurance Data |
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| 作者姓名： | AndreasChristmann |
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| 作者单位： | Department of |
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| 摘 要： | 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. We use a nonparametric approach based on a combination of kernel logistic regression and ε-support vector regression which both have good robustness properties. The strategy is applied to a data set from motor vehicle insurance companies.
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| 关 键 词： | 数字化矿业 核函数逻辑回归 数理统计 机器学习 变量支持 |
| 收稿时间： | 5 April 2004 |
On a Strategy to Develop Robust and Simple Tariffs from Motor Vehicle Insurance Data |
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| AndreasChristmann.On a Strategy to Develop Robust and Simple Tariffs from Motor Vehicle Insurance Data[J].Acta Mathematicae Applicatae Sinica,2005,21(2):193-208. |
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| Authors: | Andreas Christmann |
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| Institution: | (1) Department of Statistics, University of Dortmund, D-44221 Dortmund, Germany |
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| Abstract: | 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. We use a nonparametric approach based on a combination of kernel logistic regression and ε-support vector
regression which both have good robustness properties. The strategy is applied to a data set from motor vehicle insurance
companies. |
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| Keywords: | Data mining kernel logistic regression robustness statistical machine learning support vector regression |
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