Package: cpi 0.1.4

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]

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cpi.pdf |cpi.html✨
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Bug tracker:https://github.com/bips-hb/cpi/issues

On CRAN:

1 exports 11 stars 1.59 score 35 dependencies 24 scripts 179 downloads

Last updated 2 years agofrom:f2feb8f83f. Checks:OK: 1 NOTE: 6. Indexed: yes.

Exports:cpi

Dependencies:backportscheckmatecodetoolscorpcordata.tabledigestevaluateforeachfuturefuture.applyglmnetglobalsgtoolsiteratorsknockofflatticelgrlistenvMatrixmlbenchmlr3mlr3measuresmlr3miscpalmerpenguinsparadoxparallellyPRROCR6RcppRcppEigenRdsdpRSpectrashapesurvivaluuid