Reduction of Risk Factors in Risk Assessment: An Identification Tree Approach - Volume 3 Number 2 (Apr. 2013) - ijmo
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General Information
Editor-in-chief
Prof. Adrian Olaru
University Politehnica of Bucharest, Romania
I'm happy to take on the position of editor in chief of IJMO. It's a journal that shows promise of becoming a recognized journal in the area of modelling and optimization. I'll work together with the editors to help it progress.
IJMO 2013 Vol.3(2): 167-171 ISSN: 2010-3697
DOI: 10.7763/IJMO.2013.V3.260

Reduction of Risk Factors in Risk Assessment: An Identification Tree Approach

Ankit Agarwal, Jyotshna Dongardive, and Siby Abraham
Abstract—The paper proposes a unique procedure to reduce risk factors in risk assessment. It offers a variant of decision tree called Identification tree for reducing number of risk factors used in assessment. The model, which uses auto insurance as a case study, employs historical evidences of different vehicles as risk factors. The work offers reduction of original risk factors from a set of twenty three to a reduced set of nine risk factors. The model was validated using real time and industry specific data.

Index Terms—Average disorder score, identification tree, risk assessment, risk factor.

Ankit Agarwal and Jyotsna Dongerdive are with the University Department of Computer Science, University of Mumbai, India (e-mail: ankit.g.agarwal@gmail.com, jyotss.d@gmail.com).
Siby Abraham is with the Department of Mathematics & Statistics, Guru Nanak Khalsa College, University of Mumbai, India (e-mail: sibyam@gmail.com).

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Cite:Ankit Agarwal, Jyotshna Dongardive, and Siby Abraham, "Reduction of Risk Factors in Risk Assessment: An Identification Tree Approach," International Journal of Modeling and Optimization vol. 3, no. 2, pp. 167-171, 2013.

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