MKclass: Statistical Classification

Performance measures and scores for statistical classification such as accuracy, sensitivity, specificity, recall, similarity coefficients, AUC, GINI index, Brier score and many more. Calculation of optimal cut-offs and decision stumps (Iba and Langley (1991), <doi:10.1016/B978-1-55860-247-2.50035-8>) for all implemented performance measures. Hosmer-Lemeshow goodness of fit tests (Lemeshow and Hosmer (1982), <doi:10.1093/oxfordjournals.aje.a113284>; Hosmer et al (1997), <doi:10.1002/(SICI)1097-0258(19970515)16:9%3C965::AID-SIM509%3E3.0.CO;2-O>). Statistical and epidemiological risk measures such as relative risk, odds ratio, number needed to treat (Porta (2014), <doi:10.1093%2Facref%2F9780199976720.001.0001>).

Version: 0.3
Depends: R (≥ 4.0.0)
Imports: stats
Suggests: knitr, rmarkdown, foreach, parallel, doParallel
Published: 2020-10-10
Author: Matthias Kohl ORCID iD [aut, cre]
Maintainer: Matthias Kohl <Matthias.Kohl at>
License: LGPL-3
NeedsCompilation: no
Citation: MKclass citation info
Materials: NEWS
CRAN checks: MKclass results


Reference manual: MKclass.pdf
Vignettes: MKclass
Package source: MKclass_0.3.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): MKclass_0.3.tgz, r-release (x86_64): MKclass_0.3.tgz, r-oldrel: MKclass_0.3.tgz


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