wconf: Weighted Confusion Matrix

Allows users to create weighted confusion matrices and accuracy metrics that help with the model selection process for classification problems, where distance from the correct category is important. The package includes several weighting schemes which can be parameterized, as well as custom configuration options. Furthermore, users can decide whether they wish to positively or negatively affect the accuracy score as a result of applying weights to the confusion matrix. 'wconf' integrates well with the 'caret' package, but it can also work standalone when provided data in matrix form. References: Kuhn, M. (2008) "Building Perspective Models in R Using the caret Package" <doi:10.18637/jss.v028.i05> Monahov, A. (2021) "Model Evaluation with Weighted Threshold Optimization (and the mewto R package)" <doi:10.2139/ssrn.3805911> Van de Velden, M., Iodice D'Enza, A., Markos, A., Cavicchia, C. (2023) "A general framework for implementing distances for categorical variables" <doi:10.48550/arXiv.2301.02190>.

Version: 1.0.0
Suggests: knitr, rmarkdown, caret
Published: 2023-12-12
Author: Alexandru Monahov ORCID iD [aut, cre, cph]
Maintainer: Alexandru Monahov <alexandru.monahov at proton.me>
License: CC BY-SA 4.0
URL: https://www.alexandrumonahov.eu.org/projects
NeedsCompilation: no
Materials: README NEWS
CRAN checks: wconf results


Reference manual: wconf.pdf
Vignettes: wconf: Weighted Confusion Matrix


Package source: wconf_1.0.0.tar.gz
Windows binaries: r-prerel: wconf_1.0.0.zip, r-release: wconf_1.0.0.zip, r-oldrel: wconf_1.0.0.zip
macOS binaries: r-prerel (arm64): wconf_1.0.0.tgz, r-release (arm64): wconf_1.0.0.tgz, r-oldrel (arm64): wconf_1.0.0.tgz, r-prerel (x86_64): wconf_1.0.0.tgz, r-release (x86_64): wconf_1.0.0.tgz


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