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 |
| DOI: |
10.32614/CRAN.package.EIX |
| 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:
Downloads:
Reverse dependencies:
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