The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.

CalibratR: Mapping ML Scores to Calibrated Predictions

Transforms your uncalibrated Machine Learning scores to well-calibrated prediction estimates that can be interpreted as probability estimates. The implemented BBQ (Bayes Binning in Quantiles) model is taken from Naeini (2015, ISBN:0-262-51129-0). Please cite this paper: Schwarz J and Heider D, Bioinformatics 2019, 35(14):2458-2465.

Version: 0.1.2
Depends: R (≥ 2.10.0)
Imports: ggplot2, pROC, reshape2, parallel, foreach, stats, fitdistrplus, doParallel
Published: 2019-08-19
DOI: 10.32614/CRAN.package.CalibratR
Author: Johanna Schwarz, Dominik Heider
Maintainer: Dominik Heider <heiderd at mathematik.uni-marburg.de>
License: LGPL-3
NeedsCompilation: no
Citation: CalibratR citation info
CRAN checks: CalibratR results

Documentation:

Reference manual: CalibratR.pdf

Downloads:

Package source: CalibratR_0.1.2.tar.gz
Windows binaries: r-devel: CalibratR_0.1.2.zip, r-release: CalibratR_0.1.2.zip, r-oldrel: CalibratR_0.1.2.zip
macOS binaries: r-release (arm64): CalibratR_0.1.2.tgz, r-oldrel (arm64): CalibratR_0.1.2.tgz, r-release (x86_64): CalibratR_0.1.2.tgz, r-oldrel (x86_64): CalibratR_0.1.2.tgz
Old sources: CalibratR archive

Reverse dependencies:

Reverse suggests: ENMTools

Linking:

Please use the canonical form https://CRAN.R-project.org/package=CalibratR 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.