Performance of classification models from a user perspective
Performance of classification models from a user perspective
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.
data mining, classification, metrics, justifiability, comprehensibility
782-793
Martens, David
42e7e141-fb3d-4ead-8e3a-96b39bab65f9
Vanthienen, Jan
6f3d818f-0fce-46fa-966b-160e645caf6d
Verbeke, Wouter
57c0d98a-130a-4202-b6dd-cdc6914f4732
Baesens, Bart
f7c6496b-aa7f-4026-8616-ca61d9e216f0
November 2011
Martens, David
42e7e141-fb3d-4ead-8e3a-96b39bab65f9
Vanthienen, Jan
6f3d818f-0fce-46fa-966b-160e645caf6d
Verbeke, Wouter
57c0d98a-130a-4202-b6dd-cdc6914f4732
Baesens, Bart
f7c6496b-aa7f-4026-8616-ca61d9e216f0
Martens, David, Vanthienen, Jan, Verbeke, Wouter and Baesens, Bart
(2011)
Performance of classification models from a user perspective.
[in special issue: Recent Advances in Data, Text, and Media Mining & Information Issues in Supply Chain and in Service System Design]
Decision Support Systems, 51 (4), .
(doi:10.1016/j.dss.2011.01.013).
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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Published date: November 2011
Keywords:
data mining, classification, metrics, justifiability, comprehensibility
Organisations:
Southampton Business School
Identifiers
Local EPrints ID: 336476
URI: http://eprints.soton.ac.uk/id/eprint/336476
ISSN: 0167-9236
PURE UUID: 2202cd8c-f9c9-4eb7-ba28-29bf21dec699
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Date deposited: 27 Mar 2012 12:45
Last modified: 15 Mar 2024 03:20
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Contributors
Author:
David Martens
Author:
Jan Vanthienen
Author:
Wouter Verbeke
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