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.
Package details |
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Maintainer | |
License | GPL |
Version | 2.3.0 |
URL | https://ModelOriented.github.io/DALEXtra/ https://github.com/ModelOriented/DALEXtra |
Package repository | View on GitHub |
Installation |
Install the latest version of this package by entering the following in R:
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