Performance of classification models from a user perspective |
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| Authors: | David Martens Jan Vanthienen Wouter Verbeke Bart Baesens[Author vitae] |
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| Affiliation: | aDepartment of Environment, Technology and Technology Management, University of Antwerp, Prinsstraat 13, B-2000 Antwerp, Belgium;bDepartment of Decision Sciences and Information Management, Katholieke Universiteit Leuven, Naamsestraat 69, B-3000 Leuven, Belgium;cSchool of Management, University of Southampton, Highfield Southampton, SO17 1BJ, United Kingdom;dVlerick, Leuven-Gent Management School, Reep 1, B-9000 Ghent, Belgium |
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| Abstract: | This paper proposes a complete framework to assess the overall performance of classification models from a user perspective in terms of accuracy, comprehensibility, and justifiability. A review is provided of accuracy and comprehensibility measures, and a novel metric is introduced that allows one to measure the justifiability of classification models. Furthermore, taxonomy of domain constraints is introduced, and an overview of the existing approaches to impose constraints and include domain knowledge in data mining techniques is presented. Finally, justifiability metric is applied to a credit scoring and customer churn prediction case. |
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| Keywords: | Data mining Classification Metrics Justifiability Comprehensibility |
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