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.
Version: |
2.2.1 |
Depends: |
R (≥ 3.5.0), DALEX (≥ 2.4.0) |
Imports: |
reticulate, ggplot2 |
Suggests: |
auditor, gbm, ggrepel, h2o, iml, ingredients, lime, localModel, mlr, mlr3, ranger, recipes, rmarkdown, rpart, stacks, xgboost, testthat, tidymodels |
Published: |
2022-06-14 |
Author: |
Szymon Maksymiuk
[aut, cre],
Przemyslaw Biecek
[aut],
Hubert Baniecki [aut],
Anna Kozak [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 |
Citation: |
DALEXtra citation info |
Materials: |
NEWS |
CRAN checks: |
DALEXtra results |
Documentation:
Downloads:
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