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, 'java' 'h2o' library and 'mljar' API. 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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0.2.0 by Szymon Maksymiuk, 17 days 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] , Katarzyna Pekala [aut] , Anna Kozak [ctb]

Documentation:   PDF Manual  

GPL license

Imports reticulate, ggplot2, glmnet, ggdendro, gridExtra

Depends on DALEX

Suggests auditor, ingredients, gbm, ggrepel, h2o, mljar, mlr, mlr3, randomForest, rmarkdown, rpart, xgboost, testthat

See at CRAN