Package: vivo 0.2.1

Anna Kozak

vivo: Variable Importance via Oscillations

Provides an easy to calculate local variable importance measure based on Ceteris Paribus profile and global variable importance measure based on Partial Dependence Profiles.

Authors:Anna Kozak [aut, cre], Przemyslaw Biecek [aut, ths]

vivo_0.2.1.tar.gz
vivo_0.2.1.zip(r-4.7)vivo_0.2.1.zip(r-4.6)vivo_0.2.1.zip(r-4.5)
vivo_0.2.1.tgz(r-4.6-any)vivo_0.2.1.tgz(r-4.5-any)
vivo_0.2.1.tar.gz(r-4.7-any)vivo_0.2.1.tar.gz(r-4.6-any)
vivo_0.2.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
vivo/json (API)

# Install 'vivo' in R:
install.packages('vivo', repos = c('https://modeloriented.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/modeloriented/vivo/issues

On CRAN:

Conda:

explainable-aiexplainable-artificial-intelligenceexplainable-mlimlinterpretable-machine-learningvariable-importancexai

5.45 score 14 stars 7 scripts 319 downloads 2 mentions 4 exports 32 dependencies

Last updated from:dda6ffbb11. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK149
source / vignettesOK229
linux-release-x86_64OK188
macos-release-arm64OK165
macos-oldrel-arm64OK122
windows-develOK97
windows-releaseOK103
windows-oldrelOK100
wasm-releaseOK128

Exports:calculate_variable_splitcalculate_weightglobal_variable_importancelocal_variable_importance

Dependencies:clicodetoolscpp11DALEXdigestdoFuturefarverforeachfuturefuture.applyggplot2globalsgluegridExtragtableiBreakDowningredientsisobanditeratorskernelshaplabelinglifecyclelistenvparallellyR6RColorBrewerrlangS7scalesvctrsviridisLitewithr

Example of global variable importance
1 Dataset | 2 Random forest regression model | 3 Calculate Partial Dependence Profiles | 4 Calculate measure of global variable importance | 5 Comparison of the importance of variables for two or more models
Rendered fromvignette_apartments_global.Rmdusingknitr::rmarkdown

Last update: 2020-07-01
Started: 2020-07-01

Example of local variable importance
1 Dataset | 2 Random forest regression model | 3 New observation | 4 Calculate Ceteris Paribus profiles | 5 Calculate measure of local variable importance | 6 Comparison of two or more methods of calculating the importance of variables | 7 Comparison of the importance of variables for two or more models
Rendered fromvignette_apartments_local.Rmdusingknitr::rmarkdown

Last update: 2020-07-01
Started: 2020-07-01