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Computational Statistics

, Volume 16, Issue 3, pp 373–386 | Cite as

Bump Hunting for Risk: a New Data Mining Tool and its Applications

  • Ursula Becker
  • Ludwig Fahrmeir
Article

Summary

Bump Hunting is a new data mining technique (Friedman, J. H. & Fisher, N. I. 1999). In this paper we explore its potential for risk assessment. The method is first presented and illustrated by application to credit risk data from a German bank. Based on comparisons with standard analyses of this data set, we conclude that Bump Hunting has potential for identification of risk in financial applications. In the next step the original Bump Hunting algorithm is modified for analysis of censored survival data. This Survival Bump Hunting is used for the analysis of a bone marrow transplant data set and these results are compared to previous analyses which used standard survival methods such as Cox regression. The findings obtained using Survival Bump Hunting confirmed the previous analyses and added some interesting new aspects.

Keywords

Data Mining Bump Hunting High-dimensional data Classification Credit scoring Survival analysis Prognostic factors 

References

  1. Becker, U. (1999), Bump Hunting: A New Data Mining Tool, Ludwig-Maximilians-Universität München, Institut für Statistik, Diploma thesis.Google Scholar
  2. Fahrmeir, L. & Hamerle, A. (1984), Multivariate statistische Verfahren. De Gruyter, Berlin.zbMATHGoogle Scholar
  3. Friedman, J. H. & Fisher, N. I. (1999), Bump hunting in high-dimensional data, Statistics and Computing 9 (2), 123–143.CrossRefGoogle Scholar
  4. Hofmann, H.-J. (1990), Die Anwendung des CART-Verfahrens zur statistischen Bonitätsanalyse von Konsumentenkrediten, Zeitschrift für Betriebswirtschaft 9B, 941–961.Google Scholar
  5. Lee, E. T. (1992), Statistical Methods for Survival Data Analysis, John Wiley & Sons, New York.Google Scholar
  6. Michie, D., Spiegelhalter, D. J. & Taylor, C. C. (1994), Machine Learning, Neural and Statistical Classification. Ellis Horwood Series in Artificial Intelligence, New York.Google Scholar
  7. Szydlo et. al. (1997), Results of allogeneic bone marrow transplants for leukemia using donors other than HLA-identical siblings. Journal of Clinical Oncology 15, 1767–1777.CrossRefGoogle Scholar

Copyright information

© Physica-Verlag 2001

Authors and Affiliations

  • Ursula Becker
    • 1
  • Ludwig Fahrmeir
    • 1
  1. 1.Department of StatisticsUniversity of MunichMünchenGermany

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