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: 1.0-2
Depends: R (≥ 2.10)
Suggests: MASS, class, testthat
Published: 2019-02-26
DOI: 10.32614/CRAN.package.hmeasure
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_1.0-2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): hmeasure_1.0-2.tgz, r-oldrel (arm64): hmeasure_1.0-2.tgz, r-release (x86_64): hmeasure_1.0-2.tgz, r-oldrel (x86_64): hmeasure_1.0-2.tgz
Old sources: hmeasure archive

Reverse dependencies:

Reverse depends: fscaret


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