Package: shapper 0.1.4

Szymon Maksymiuk

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:Szymon Maksymiuk [aut, cre], Alicja Gosiewska [aut], Przemyslaw Biecek [aut], Mateusz Staniak [ctb], Michal Burdukiewicz [ctb]

shapper_0.1.4.tar.gz
shapper_0.1.4.zip(r-4.7)shapper_0.1.4.zip(r-4.6)shapper_0.1.4.zip(r-4.5)
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-4.7-any)shapper_0.1.4.tar.gz(r-4.6-any)
shapper_0.1.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html
DESCRIPTION |NEWS
card.svg |card.png
shapper/json (API)

# 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

On CRAN:

Conda:

7.40 score 58 stars 73 scripts 582 downloads 4 exports 42 dependencies

Last updated from:3b54449553. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK169
source / vignettesOK230
linux-release-x86_64OK169
macos-release-arm64OK124
macos-oldrel-arm64OK89
windows-develOK153
windows-releaseOK153
windows-oldrelOK151
wasm-releaseOK117

Exports:individual_variable_effectinstall_shapshaptheme_drwhy_colors

Dependencies:clicodetoolscpp11DALEXdigestdoFuturefarverforeachfuturefuture.applyggplot2globalsgluegridExtragtablehereiBreakDowningredientsisobanditeratorsjsonlitekernelshaplabelinglatticelifecyclelistenvMatrixparallellypngR6rappdirsRColorBrewerRcppRcppTOMLreticulaterlangrprojrootS7scalesvctrsviridisLitewithr

How to use shapper for classification
Introduction | Python library shap | Load data sets | Let's build models | Here shapper starts | Plotting results | Let's filter data for plot

Last update: 2023-05-25
Started: 2018-12-14

How to use shapper for regression
Introduction | Install shaper and shap | R package shapper | Python library shap | Load data sets | Let's build a model | Prediction to be explained | Here shapper starts | Plotting results

Last update: 2021-06-30
Started: 2018-12-14

Readme and manuals

Help Manual

Help pageTopics
Individual Variable Effectindividual_variable_effect individual_variable_effect.default individual_variable_effect.explainer shap
Install shap Python libraryinstall_shap
Plots Attributions for Variables of Individual Predictionplot.individual_variable_effect
Print Individual Variable Effectsprint.individual_variable_effect
DrWhy Theme for ggplot objectstheme_drwhy_colors