Key papers on H-measure

• D.J. Hand and C. Anagnostopoulos. When is the area under the receiver operating characteristic curve an appropriate measure of classifier performance? Pattern Recognition Letters, 34:492–496, 2013.
• D.J. Hand. Measuring classifier performance: a coherent alternative to the area under the ROC curve. Machine Learning, 77:103–123, 2009.
• D.J. Hand. Evaluating diagnostic tests: the area under the ROC curve and the balance of errors. Statistics in Medicine, 29:1502–1510, 2010.

Review papers on classification performance

• N.M. Adams and D.J. Hand. Comparing classifiers when the misallocation costs are uncertain. Pattern Recognition, 32:1139–1147, 1999.
• N.M. Adams and D.J. Hand. An improved method for comparing diagnostic tests. Journal of Computing in Biology and Medicine, 30:89–96, 2000.
• N.M. Adams and D.J. Hand. Improving the practice of classifier performance assessment. Neural Computation, 12:305–311, 2000.
• D.J. Hand. Assessing classification rules. The Journal of Applied Statistics, pages 3–16, 1994.
• D.J. Hand. Measuring diagnostic accuracy of statistical prediction rules. Statistica Neerlandica, 53:3–16., 2001.
• J. Hilden. The area under the ROC curve and its competitors. Medical Decision Making, 11:95–101, 1991.
• A. Jamain and D.J. Hand. Mining supervised classification performance studies: a meta-analytic investigation. Journal of Classification, 25:87–112, 2008.
• W.J. Krzanowski and D.J. Hand. ROC curves for continuous data. Chapman and Hall, 2009.