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.