explainer: Machine Learning Model Explainer

It enables detailed interpretation of complex classification and regression models through Shapley analysis including data-driven characterization of subgroups of individuals. Furthermore, it facilitates multi-measure model evaluation, model fairness, and decision curve analysis. Additionally, it offers enhanced visualizations with interactive elements.

Version: 1.0.0
Imports: cvms, data.table, dplyr, egg, ggplot2, ggpmisc, ggpubr, magrittr, plotly, tibble, tidyr, writexl
Suggests: cowplot, mlr3, mlr3learners, knitr, broom, iml, forcats, mlr3viz, plotROC, psych, reshape2, remotes, mlbench, ranger, precrec
Published: 2023-12-15
Author: Ramtin Zargari Marandi ORCID iD [aut, cre]
Maintainer: Ramtin Zargari Marandi <ramtin.zargari.marandi at regionh.dk>
BugReports: https://github.com/PERSIMUNE/explainer/issues
License: MIT + file LICENSE
URL: https://persimune.github.io/explainer/, https://github.com/PERSIMUNE/explainer
NeedsCompilation: no
Materials: README
CRAN checks: explainer results

Documentation:

Reference manual: explainer.pdf

Downloads:

Package source: explainer_1.0.0.tar.gz
Windows binaries: r-prerel: explainer_1.0.0.zip, r-release: explainer_1.0.0.zip, r-oldrel: explainer_1.0.0.zip
macOS binaries: r-prerel (arm64): explainer_1.0.0.tgz, r-release (arm64): explainer_1.0.0.tgz, r-oldrel (arm64): explainer_1.0.0.tgz, r-prerel (x86_64): explainer_1.0.0.tgz, r-release (x86_64): explainer_1.0.0.tgz

Linking:

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