survshap 0.4.0

Implementation of the SurvSHAP(t) explanation method for time-dependent explainability of machine learning survival models

survshap

Overview

The survshap package contains an implementation of the SurvSHAP(t) method, the first time-dependent explanation method for interpreting survival black-box models. It is based on SHapley Additive exPlanations (SHAP) but extends it to the time-dependent setting of survival analysis. SurvSHAP(t) is able to detect time-dependent variable effects and its aggregation determines the local variable importance.

Read more about SurvSHAP(t) in our paper.

Installation

pip install survshap

Citation

If you use this package, please cite our paper:

@article{survshap,
    title = {SurvSHAP(t): Time-dependent explanations of machine learning survival models},
    journal = {Knowledge-Based Systems},
    volume = {262},
    pages = {110234},
    year = {2023},
    issn = {0950-7051}
    }