DALEXtra: 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) <arXiv:1806.08915> 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.

Version:	1.3.2
Depends:	R (≥ 3.5.0), DALEX (≥ 1.3)
Imports:	reticulate, ggplot2, glmnet, ggdendro, gridExtra
Suggests:	auditor, ingredients, gbm, ggrepel, h2o, mlr, mlr3, randomForest, rmarkdown, rpart, xgboost, testthat, covr
Published:	2020-07-28
Author:	Szymon Maksymiuk [aut, cre], Przemyslaw Biecek [aut], Katarzyna Pekala [aut], Anna Kozak [ctb], Hubert Baniecki [ctb]
Maintainer:	Szymon Maksymiuk <sz.maksymiuk at gmail.com>
BugReports:	https://github.com/ModelOriented/DALEXtra/issues
License:	GPL-2 | GPL-3 [expanded from: GPL]
URL:	https://ModelOriented.github.io/DALEXtra/, https://github.com/ModelOriented/DALEXtra
NeedsCompilation:	no
Materials:	NEWS
CRAN checks:	DALEXtra results

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