hmeasure: The H-Measure and Other Scalar Classification Performance Metrics

Classification performance metrics that are derived from the ROC curve of a classifier. The package includes the H-measure performance metric as described in <>, 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.

Version: 1.0-1
Depends: R (≥ 2.10)
Suggests: MASS, class, testthat
Published: 2019-01-02
Author: Christoforos Anagnostopoulos and David J. Hand
Maintainer: Christoforos Anagnostopoulos <christoforos.anagnostopoulos06 at>
License: MIT + file LICENSE
NeedsCompilation: no
Materials: README NEWS
CRAN checks: hmeasure results


Reference manual: hmeasure.pdf
Vignettes: hmeasure
Package source: hmeasure_1.0-1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X binaries: r-release: hmeasure_1.0-1.tgz, r-oldrel: hmeasure_1.0.tgz
Old sources: hmeasure archive

Reverse dependencies:

Reverse depends: fscaret
Reverse suggests: rattle


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