survex: Explainable Machine Learning in Survival Analysis

Survival analysis models are commonly used in medicine and other areas. Many of them are too complex to be interpreted by human. Exploration and explanation is needed, but standard methods do not give a broad enough picture. 'survex' provides easy-to-apply methods for explaining survival models, both complex black-boxes and simpler statistical models. They include methods specific to survival analysis such as SurvSHAP(t) described in Krzyzinski et al., (2022) <arXiv:2208.11080>, SurvLIME introduced in Kovalev et al., (2020) <doi:10.1016/j.knosys.2020.106164> as well as extensions of existing ones described in Biecek et al., (2021) <doi:10.1201/9780429027192>.

Version: 0.2.2
Depends: R (≥ 3.5.0)
Imports: DALEX (≥ 2.2.1), ggplot2, pec, survival, patchwork
Suggests: censored, covr, gbm, generics, glmnet, ingredients, knitr, mboost, parsnip, progressr, randomForestSRC, ranger, rmarkdown, testthat (≥ 3.0.0), withr, xgboost
Published: 2022-12-01
Author: Mikołaj Spytek [aut, cre], Mateusz Krzyziński [aut], Hubert Baniecki ORCID iD [aut], Przemyslaw Biecek ORCID iD [aut]
Maintainer: Mikołaj Spytek <mikolajspytek at>
License: GPL (≥ 3)
NeedsCompilation: no
Materials: README NEWS
CRAN checks: survex results


Reference manual: survex.pdf
Vignettes: Creating custom explainers
Package usage


Package source: survex_0.2.2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): survex_0.2.2.tgz, r-oldrel (arm64): survex_0.2.2.tgz, r-release (x86_64): survex_0.2.2.tgz, r-oldrel (x86_64): survex_0.2.2.tgz
Old sources: survex archive


Please use the canonical form to link to this page.