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.


Reference manual

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1.2.0 by Szymon Maksymiuk, 8 months ago


Report a bug at https://github.com/ModelOriented/EIX/issues

Browse source code at https://github.com/cran/EIX

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

Documentation:   PDF Manual  

GPL-2 license

Imports MASS, ggplot2, data.table, purrr, xgboost, DALEX, ggrepel, ggiraphExtra, iBreakDown, tidyr, scales

Suggests Matrix, knitr, rmarkdown, lightgbm

See at CRAN