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) 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. Third branch of 'DALEXtra' package is aspect importance analysis that provides instance-level explanations for the groups of explanatory variables.


Reference manual

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2.1.1 by Szymon Maksymiuk, 5 months ago

https://ModelOriented.github.io/DALEXtra/, https://github.com/ModelOriented/DALEXtra

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

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

Authors: Szymon Maksymiuk [aut, cre] , Przemyslaw Biecek [aut] , Anna Kozak [ctb] , Hubert Baniecki [ctb]

Documentation:   PDF Manual  

GPL license

Imports reticulate, ggplot2

Depends on DALEX

Suggests auditor, ingredients, gbm, ggrepel, h2o, iml, lime, localModel, mlr, mlr3, randomForest, recipes, rmarkdown, rpart, xgboost, testthat, tidymodels

See at CRAN