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 236 downloads 1 exports 35 dependencies

Last updated 3 months agofrom:238e428d7a. Checks:8 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 23 2025
R-4.5-winOKFeb 23 2025
R-4.5-macOKFeb 23 2025
R-4.5-linuxOKFeb 23 2025
R-4.4-winOKFeb 23 2025
R-4.4-macOKFeb 23 2025
R-4.3-winOKFeb 23 2025
R-4.3-macOKFeb 23 2025

Exports:cpi

Dependencies:backportscheckmatecodetoolscorpcordata.tabledigestevaluateforeachfuturefuture.applyglmnetglobalsgtoolsiteratorsknockofflatticelgrlistenvMatrixmlbenchmlr3mlr3measuresmlr3miscpalmerpenguinsparadoxparallellyPRROCR6RcppRcppEigenRdsdpRSpectrashapesurvivaluuid

Introduction to the cpi package

Rendered fromintro.Rmdusingknitr::rmarkdownon Feb 23 2025.

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