Package: EIX 1.2.1

Szymon Maksymiuk

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.

Authors:Szymon Maksymiuk [aut, cre], Ewelina Karbowiak [aut], Przemyslaw Biecek [aut, ths]

EIX_1.2.1.tar.gz
EIX_1.2.1.zip(r-4.7)EIX_1.2.1.zip(r-4.6)EIX_1.2.1.zip(r-4.5)
EIX_1.2.1.tgz(r-4.6-any)EIX_1.2.1.tgz(r-4.5-any)
EIX_1.2.1.tar.gz(r-4.7-any)EIX_1.2.1.tar.gz(r-4.6-any)
EIX_1.2.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
EIX/json (API)

# Install 'EIX' in R:
install.packages('EIX', repos = c('https://modeloriented.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/modeloriented/eix/issues

Datasets:
  • HR_data - Why are our best and most experienced employees leaving prematurely?
  • titanic_data - Passengers and Crew on the RMS Titanic

On CRAN:

Conda:

5.70 score 25 stars 5 scripts 552 downloads 4 exports 89 dependencies

Last updated from:9d44e98dc6. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK238
source / vignettesOK254
linux-release-x86_64OK252
macos-release-arm64OK164
macos-oldrel-arm64OK221
windows-develOK193
windows-releaseOK242
windows-oldrelOK202
wasm-releaseOK133

Exports:importanceinteractionslollipopwaterfall

Dependencies:base64encbslibcachemclicodetoolscpp11DALEXdata.tabledatawizarddigestdoFuturedplyrevaluatefarverfastmapfontawesomefontBitstreamVerafontLiberationfontquiverforeachfsfuturefuture.applygdtoolsgenericsggiraphggiraphExtraggplot2ggrepelglobalsgluegridExtragtablehighrhtmltoolshtmlwidgetsiBreakDowningredientsinsightisobanditeratorsjquerylibjsonlitekernelshapknitrlabelinglatticelifecyclelistenvmagrittrMASSMatrixmemoisemgcvmimemycornlmeparallellypillarpkgconfigplyrppcorpurrrR6rappdirsRColorBrewerRcppreshape2rlangrmarkdownS7sassscalessjlabelledsjmiscstringistringrsystemfontstibbletidyrtidyselecttinytexutf8vctrsviridisLitewithrxfunxgboostyaml

EIX: Explain Interactions in XGBoost
Data Info | Xgboost model creation | Model visualization | Interactions | Variables' and interactions’ importance | Explanation of single prediction including interactions
Rendered fromEIX.Rmdusingknitr::rmarkdown

Last update: 2026-01-12
Started: 2018-12-12

EIX: Titanic data
Data Info | Xgboost model creation | Model visualization | Interactions | Variables' and interactions’ importance | Explanation of the single prediction including interactions
Rendered fromtitanic_data.Rmdusingknitr::rmarkdown

Last update: 2026-01-12
Started: 2019-05-01