An Improved Model Selection Heuristic for AUC

Wu, Shaomin and Flach, P. and Ferri, C. (2007) An Improved Model Selection Heuristic for AUC. In: 18th European Conference on Machine Learning, ECML 2007, 17-21 September 2007, Warsaw. (The full text of this publication is not available from this repository)

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Abstract

The area under the ROC curve (AUC) has been widely used to measure ranking performance for binary classification tasks. AUC only employs the classifier's scores to rank the test instances; thus, it ignores other valuable information conveyed by the scores, such as sensitivity to small differences in the score values. However, as such differences are inevitable across samples, ignoring them may lead to overfitting the validation set when selecting models with high AUC. This problem is tackled in this paper. On the basis of ranks as well as scores, we introduce a new metric called scored AUC (sAUC), which is the area under the sROC curve. The latter measures how quickly AUC deteriorates if positive scores are decreased. We study the interpretation and statistical properties of sAUC. Experimental results on UCI data sets convincingly demonstrate the effectiveness of the new metric for classifier evaluation and selection in the case of limited validation data. © Springer-Verlag Berlin Heidelberg 2007.

Item Type: Conference or workshop item (Paper)
Additional information: Unmapped bibliographic data: PY - 2007/// [EPrints field already has value set] AD - Cranfield University, United Kingdom [Field not mapped to EPrints] AD - University of Bristol, United Kingdom [Field not mapped to EPrints] AD - Universitat Politècnica de València, Spain [Field not mapped to EPrints] JA - Lect. Notes Comput. Sci. [Field not mapped to EPrints]
Uncontrolled keywords: Database systems, Heuristic methods, Mathematical models, Problem solving, Sensitivity analysis, Statistical methods, Binary classification tasks, Classifier evaluation, Data sets, Statistical properties, Classification (of information)
Subjects: H Social Sciences
H Social Sciences > HA Statistics > HA33 Management Science
Divisions: Faculties > Social Sciences > Kent Business School
Faculties > Social Sciences > Kent Business School > Management Science
Depositing User: Shaomin Wu
Date Deposited: 28 Sep 2012 15:26
Last Modified: 17 Apr 2014 09:39
Resource URI: http://kar.kent.ac.uk/id/eprint/31016 (The current URI for this page, for reference purposes)
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