Classification performance metrics that are derived from the ROC curve of a classifier. The package includes the H-measure performance metric as described in <http://link.springer.com/article/10.1007/s10994-009-5119-5>, which computes the minimum total misclassification cost, integrating over any uncertainty about the relative misclassification costs, as per a user-defined prior. It also offers a one-stop-shop for other scalar metrics of performance, including sensitivity, specificity and many others, and also offers plotting tools for ROC curves and related statistics.
|Author||Christoforos Anagnostopoulos <email@example.com> and David J. Hand <firstname.lastname@example.org>|
|Maintainer||Christoforos Anagnostopoulos <email@example.com>|
|License||MIT + file LICENSE|
|Package repository||View on GitHub|
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