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
Full text not available from this repository.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 |
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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 |
SWORD Depositor: | Elements |
Depositing User: | Elements |
Date Deposited: | 30 Jun 2015 20:26 |
Last Modified: | 06 Jan 2022 14:39 |
URI: | http://repository.essex.ac.uk/id/eprint/13965 |
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