Relative cost curves: An alternative to AUC and an extension to 3-class problems

Kybernetika

Volumn 50, Issue 5, 2014, Pages 647-660

  Montvida, Olga ^a   Klawonn, Frank ^b,c  

^a UNIVERSITY OF LATVIA   (Latvia)

^b HELMHOLTZ CENTRE FOR INFECTION RESEARCH   (Germany)

^c OSTFALIA UNIVERSITY OF APPLIED SCIENCES   (Germany)

Author keywords

AUC; Classifier; Cost curves; Misclassification costs; Performance evaluation; ROC curves

Indexed keywords

EID: 84919485856     PISSN: 00235954     EISSN: 1805949X     Source Type: Journal    
DOI: 10.14736/kyb-2014-5-0647     Document Type: Article

References (12)

1. A.P. Bradley: The use of the area under the ROC curve in the evaluation of machine learning algorithms. Pattern Recognition 30 (1997), 1145-1159.
2. C. Drummond and R. C. Holte: Cost curves: An improved method for visualizing classifier performance. Machine Learning 65 (2006) 95-130.
3. T. Fawcett: An introduction to roc analysis. Pattern Recognition Lett. 27 (2006), 861-874.
4. D. J. Hand: Measuring classifier performance: a coherent alternative to the area under the ROC curve. Machine Learning 77 (2009), 103-123.
5. D. J. Hand and R. J. Till: A simple generalisation of the area under the ROC curve for multiple class classification problems. Machine Learning 45 (2001), 171-186.
6. J. A. Hanley: Receiver operating characteristic (ROC) methodology: the state of the art. Critical Reviews in Diagnostic Imaging 29 (1989), 307-335.
7. J. Hernández-Orallo, P. Flach, and C. Ferri: Brier curves: a new cost-based visualisation of classifier performance. In: Proc. 28th International Conference on Machine Learning (ICML-11) (L. Getoor and T. Scheffer, eds.), ACM, New York 2011, pp. 585-592.
8. F. Klawonn, F. Höppner, and S. May: An alternative to ROC and AUC analysis of classifiers. In: Advances in Intelligent Data Analysis X, (J. Gama, E. Bradley, and J. Hollmén, eds.), Springer, Berlin 2011, p. 210-221.
9. W. J. Krzanowski and D. J. Hand: ROC Curves for Continuous data. Chapman and Hall, London 2009.
10. J. Li and J.P. Fine: ROC analysis with multiple classes and multiple tests: methodology and its application in microarray studies. Biostatistics 9 (2008), 566-576.
11. P. M. Murphy and D. W. Aha: Uci repository of machine learning databases. 1992. Avaible: http://archive.ics.uci.edu/ml/datasets/Breast+Cancer+Wisconsin+(Diagnostic).
12. D. Mossman: Three-way ROCs. Medical Decision Making 19 (1999), 78-89.