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) introduced in Krzyzinski et al., (2023) doi:10.1016/j.knosys.2022.110234, SurvLIME described 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.
- Version1.2.0
- R version≥ 3.5.0
- LicenseGPL (≥ 3)
- Needs compilation?No
- survex citation info
- Last release10/24/2023
Documentation
Team
Mikołaj Spytek
Przemyslaw Biecek
Show author detailsRolesAuthorLorenz A. Kapsner
Hubert Baniecki
Show author detailsRolesAuthorMateusz Krzyziński
Sophie Langbein
Show author detailsRolesAuthor
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- Imports6 packages
- Suggests20 packages