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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.

copied from cf-post-staging / r-dalextra
Type Size Name Uploaded Downloads Labels
conda 387.0 kB | noarch/r-dalextra-2.3.0-r44hc72bb7e_2.conda  8 days and 12 hours ago 48 main
conda 385.9 kB | noarch/r-dalextra-2.3.0-r45hc72bb7e_2.conda  8 days and 12 hours ago 50 main
conda 386.3 kB | noarch/r-dalextra-2.3.0-r44hc72bb7e_1.conda  10 months and 8 days ago 784 main
conda 381.8 kB | noarch/r-dalextra-2.3.0-r43hc72bb7e_1.conda  10 months and 8 days ago 801 main
conda 381.7 kB | noarch/r-dalextra-2.3.0-r43hc72bb7e_0.conda  10 months and 10 days ago 806 main

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