DALEXtra: Extension for 'DALEX' Package

Provides wrapper of various machine learning models. In applied machine learning, there is a strong belief that we need to strike a balance between interpretability and accuracy. However, in field of the interpretable machine learning, there are more and more new ideas for explaining black-box models, that are implemented in 'R'. 'DALEXtra' creates 'DALEX' Biecek (2018) <doi:10.48550/arXiv.1806.08915> explainer for many type of models including those created using 'python' 'scikit-learn' and 'keras' libraries, and 'java' 'h2o' library. Important part of the package is Champion-Challenger analysis and innovative approach to model performance across subsets of test data presented in Funnel Plot.

Version: 2.3.0
Depends: R (≥ 3.5.0), DALEX (≥ 2.4.0)
Imports: ggplot2
Suggests: auditor, gbm, ggrepel, h2o, iml, ingredients, lime, localModel, mlr, mlr3, ranger, recipes, reticulate, rmarkdown, rpart, stacks, xgboost, testthat, tidymodels
Published: 2023-05-26
DOI: 10.32614/CRAN.package.DALEXtra
Author: Szymon Maksymiuk ORCID iD [aut, cre], Przemyslaw Biecek ORCID iD [aut], Hubert Baniecki [aut], Anna Kozak [ctb]
Maintainer: Szymon Maksymiuk <sz.maksymiuk at gmail.com>
BugReports: https://github.com/ModelOriented/DALEXtra/issues
License: GPL-2 | GPL-3 [expanded from: GPL]
URL: https://ModelOriented.github.io/DALEXtra/, https://github.com/ModelOriented/DALEXtra
NeedsCompilation: no
Citation: DALEXtra citation info
Materials: NEWS
CRAN checks: DALEXtra results


Reference manual: DALEXtra.pdf


Package source: DALEXtra_2.3.0.tar.gz
Windows binaries: r-devel: DALEXtra_2.3.0.zip, r-release: DALEXtra_2.3.0.zip, r-oldrel: DALEXtra_2.3.0.zip
macOS binaries: r-release (arm64): DALEXtra_2.3.0.tgz, r-oldrel (arm64): DALEXtra_2.3.0.tgz, r-release (x86_64): DALEXtra_2.3.0.tgz, r-oldrel (x86_64): DALEXtra_2.3.0.tgz
Old sources: DALEXtra archive

Reverse dependencies:

Reverse imports: tidysdm, viralx
Reverse suggests: marginaleffects, mlr3shiny


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