Package: cpi 0.1.5

Marvin N. Wright

cpi: Conditional Predictive Impact

A general test for conditional independence in supervised learning algorithms as proposed by Watson & Wright (2021) <doi:10.1007/s10994-021-06030-6>. Implements a conditional variable importance measure which can be applied to any supervised learning algorithm and loss function. Provides statistical inference procedures without parametric assumptions and applies equally well to continuous and categorical predictors and outcomes.

Authors:Marvin N. Wright [aut, cre], David S. Watson [aut]

cpi_0.1.5.tar.gz
cpi_0.1.5.zip(r-4.5)cpi_0.1.5.zip(r-4.4)cpi_0.1.5.zip(r-4.3)
cpi_0.1.5.tgz(r-4.5-any)cpi_0.1.5.tgz(r-4.4-any)cpi_0.1.5.tgz(r-4.3-any)
cpi_0.1.5.tar.gz(r-4.5-noble)cpi_0.1.5.tar.gz(r-4.4-noble)
cpi_0.1.5.tgz(r-4.4-emscripten)cpi_0.1.5.tgz(r-4.3-emscripten)
cpi.pdf |cpi.html
cpi/json (API)
NEWS

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

Bug tracker:https://github.com/bips-hb/cpi/issues

Pkgdown site:https://bips-hb.github.io

On CRAN:

Conda:

5.42 score 11 stars 24 scripts 207 downloads 1 exports 36 dependencies

Last updated 4 months agofrom:238e428d7a. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 25 2025
R-4.5-winOKMar 25 2025
R-4.5-macOKMar 25 2025
R-4.5-linuxOKMar 25 2025
R-4.4-winOKMar 25 2025
R-4.4-macOKMar 25 2025
R-4.4-linuxOKMar 25 2025
R-4.3-winOKMar 25 2025
R-4.3-macOKMar 25 2025

Exports:cpi

Dependencies:backportscheckmatecodetoolscorpcordata.tabledigestevaluateforeachfuturefuture.applyglmnetglobalsgtoolsiteratorsknockofflatticelgrlistenvMatrixmlbenchmlr3mlr3measuresmlr3miscpalmerpenguinsparadoxparallellyPRROCR6RcppRcppEigenRdsdprlangRSpectrashapesurvivaluuid

Introduction to the cpi package

Rendered fromintro.Rmdusingknitr::rmarkdownon Mar 25 2025.

Last update: 2022-03-02
Started: 2022-02-23