Package: fastshap 0.1.1
fastshap: Fast Approximate Shapley Values
Computes fast (relative to other implementations) approximate Shapley values for any supervised learning model. Shapley values help to explain the predictions from any black box model using ideas from game theory; see Strumbel and Kononenko (2014) <doi:10.1007/s10115-013-0679-x> for details.
Authors:
fastshap_0.1.1.tar.gz
fastshap_0.1.1.zip(r-4.5)fastshap_0.1.1.zip(r-4.4)fastshap_0.1.1.zip(r-4.3)
fastshap_0.1.1.tgz(r-4.5-x86_64)fastshap_0.1.1.tgz(r-4.5-arm64)fastshap_0.1.1.tgz(r-4.4-x86_64)fastshap_0.1.1.tgz(r-4.4-arm64)fastshap_0.1.1.tgz(r-4.3-x86_64)fastshap_0.1.1.tgz(r-4.3-arm64)
fastshap_0.1.1.tar.gz(r-4.5-noble)fastshap_0.1.1.tar.gz(r-4.4-noble)
fastshap_0.1.1.tgz(r-4.4-emscripten)fastshap_0.1.1.tgz(r-4.3-emscripten)
fastshap.pdf |fastshap.html✨
fastshap/json (API)
NEWS
# Install 'fastshap' in R: |
install.packages('fastshap', repos = c('https://bgreenwell.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/bgreenwell/fastshap/issues
Pkgdown site:https://bgreenwell.github.io
- titanic - Survival of Titanic passengers
- titanic_mice - Survival of Titanic passengers
explainable-aiexplainable-mlinterpretable-machine-learningshapleyshapley-valuesvariable-importancexaicpp
Last updated 12 months agofrom:c2fcaf794c. Checks:11 OK. Indexed: yes.
Target | Result | Latest binary |
---|---|---|
Doc / Vignettes | OK | Feb 15 2025 |
R-4.5-win-x86_64 | OK | Feb 15 2025 |
R-4.5-mac-x86_64 | OK | Feb 15 2025 |
R-4.5-mac-aarch64 | OK | Feb 15 2025 |
R-4.5-linux-x86_64 | OK | Feb 15 2025 |
R-4.4-win-x86_64 | OK | Feb 15 2025 |
R-4.4-mac-x86_64 | OK | Feb 15 2025 |
R-4.4-mac-aarch64 | OK | Feb 15 2025 |
R-4.3-win-x86_64 | OK | Feb 15 2025 |
R-4.3-mac-x86_64 | OK | Feb 15 2025 |
R-4.3-mac-aarch64 | OK | Feb 15 2025 |
Exports:explaingen_friedman
Dependencies:codetoolsforeachiteratorsRcppRcppArmadillo
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Fast approximate Shapley values | explain explain.default explain.lgb.Booster explain.lm explain.xgb.Booster |
Friedman benchmark data | gen_friedman |
Survival of Titanic passengers | titanic |
Survival of Titanic passengers | titanic_mice |