EIX: Explain Interactions in 'XGBoost'

Structure mining from 'XGBoost' and 'LightGBM' models. Key functionalities of this package cover: visualisation of tree-based ensembles models, identification of interactions, measuring of variable importance, measuring of interaction importance, explanation of single prediction with break down plots (based on 'xgboostExplainer' and 'iBreakDown' packages). To download the 'LightGBM' use the following link: <https://github.com/Microsoft/LightGBM>. 'EIX' is a part of the 'DrWhy.AI' universe.

Version: 1.2.0
Depends: R (≥ 3.5.0)
Imports: MASS, ggplot2, data.table, purrr, xgboost, DALEX, ggrepel, ggiraphExtra, iBreakDown, tidyr, scales
Suggests: Matrix, knitr, rmarkdown, lightgbm
Published: 2021-03-23
Author: Szymon Maksymiuk [aut, cre], Ewelina Karbowiak [aut], Przemyslaw Biecek [aut, ths]
Maintainer: Szymon Maksymiuk <sz.maksymiuk at gmail.com>
BugReports: https://github.com/ModelOriented/EIX/issues
License: GPL-2
URL: https://github.com/ModelOriented/EIX
NeedsCompilation: no
Materials: NEWS
CRAN checks: EIX results

Documentation:

Reference manual: EIX.pdf
Vignettes: EIX Explain Interactions in XGBoost
EIX for Titanic data

Downloads:

Package source: EIX_1.2.0.tar.gz
Windows binaries: r-devel: EIX_1.2.0.zip, r-release: EIX_1.2.0.zip, r-oldrel: EIX_1.2.0.zip
macOS binaries: r-release (arm64): EIX_1.2.0.tgz, r-release (x86_64): EIX_1.2.0.tgz, r-oldrel: EIX_1.2.0.tgz
Old sources: EIX archive

Linking:

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