Calabrese, Raffaella (2014) 'Optimal cut-off for rare events and unbalanced misclassification costs.' Journal of Applied Statistics, 41 (8). pp. 1678-1693. ISSN 0266-4763

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Abstract

This paper develops a method for handling two-class classification problems with highly unbalanced class sizes and misclassification costs. When the class sizes are highly unbalanced and the minority class represents a rare event, conventional classification methods tend to strongly favour the majority class, resulting in very low detection of the minority class. A method is proposed to determine the optimal cut-off for asymmetric misclassification costs and for unbalanced class sizes. Monte Carlo simulations show that this proposal performs better than the method based on the notion of classification accuracy. Finally, the proposed method is applied to empirical data on Italian small and medium enterprises to classify them into default and non-default groups.

Item Type:	Article
Uncontrolled Keywords:	Rare events, misclassification costs, cut-off, small and medium enterprises
Subjects:	H Social Sciences > HG Finance
Divisions:	Faculty of Social Sciences > Essex Business School Faculty of Social Sciences > Essex Business School > Essex Finance Centre
Depositing User:	Clare Chatfield
Date Deposited:	30 Jun 2015 20:26
Last Modified:	13 Nov 2015 16:33
URI:	http://repository.essex.ac.uk/id/eprint/13965

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