Package: shapper 0.1.4

shapper: Wrapper of Python Library 'shap'
Provides SHAP explanations of 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. One of the best known method for local explanations is SHapley Additive exPlanations (SHAP) introduced by Lundberg, S., et al., (2016) <arxiv:1705.07874> The SHAP method is used to calculate influences of variables on the particular observation. This method is based on Shapley values, a technique used in game theory. The R package 'shapper' is a port of the Python library 'shap'.
Authors:
shapper_0.1.4.tar.gz
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shapper_0.1.4.tgz(r-4.6-any)shapper_0.1.4.tgz(r-4.5-any)
shapper_0.1.4.tar.gz(r-4.6-any)shapper_0.1.4.tar.gz(r-4.5-any)
shapper_0.1.4.tgz(r-4.5-emscripten)
shapper.pdf |shapper.html✨
shapper/json (API)
NEWS
| # Install 'shapper' in R: |
| install.packages('shapper', repos = c('https://modeloriented.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/modeloriented/shapper/issues
Last updated from:3b54449553. Checks:9 OK. Indexed: yes.
| Target | Result | Total time | Artifact |
|---|---|---|---|
| linux-devel-x86_64 | OK | 152 | |
| source / vignettes | OK | 145 | |
| linux-release-x86_64 | OK | 141 | |
| macos-devel-arm64 | OK | 196 | |
| macos-release-arm64 | OK | 105 | |
| windows-devel | OK | 116 | |
| windows-release | OK | 122 | |
| windows-oldrel | OK | 153 | |
| wasm-release | OK | 104 |
Exports:individual_variable_effectinstall_shapshaptheme_drwhy_colors
Dependencies:clicodetoolscpp11DALEXdigestdoFuturefarverforeachfuturefuture.applyggplot2globalsgluegridExtragtablehereiBreakDowningredientsisobanditeratorsjsonlitekernelshaplabelinglatticelifecyclelistenvMatrixparallellypngR6rappdirsRColorBrewerRcppRcppTOMLreticulaterlangrprojrootS7scalesvctrsviridisLitewithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Individual Variable Effect | individual_variable_effect individual_variable_effect.default individual_variable_effect.explainer shap |
| Install shap Python library | install_shap |
| Plots Attributions for Variables of Individual Prediction | plot.individual_variable_effect |
| Print Individual Variable Effects | print.individual_variable_effect |
| DrWhy Theme for ggplot objects | theme_drwhy_colors |
