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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 <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.

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 imperial.ac.uk>
License: MIT + file LICENSE
URL: http://www.hmeasure.net
NeedsCompilation: no
Materials: README NEWS
CRAN checks: hmeasure results

Documentation:

Reference manual: hmeasure.pdf
Vignettes: hmeasure

Downloads:

Package source: hmeasure_1.0-2.tar.gz
Windows binaries: r-devel: hmeasure_1.0-2.zip, r-release: hmeasure_1.0-2.zip, r-oldrel: hmeasure_1.0-2.zip
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

Linking:

Please use the canonical form https://CRAN.R-project.org/package=hmeasure to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.