SurvSHAP(t)
This repository contains data and code for the article:
M. Krzyziński, M. Spytek, H. Baniecki, P. Biecek. SurvSHAP(t): Time-dependent explanations of machine learning survival models. Knowledge-Based Systems, 262:110234, 2023. https://doi.org/10.1016/j.knosys.2022.110234
@article{,
title = {SurvSHAP(t): Time-dependent explanations of machine learning survival models},
author = {Mateusz Krzyziński and Mikołaj Spytek and Hubert Baniecki and Przemysław Biecek},
journal = {Knowledge-Based Systems},
volume = {262},
pages = {110234},
year = {2023}
}
NOTE: SurvSHAP(t) and SurvLIME are also implemented in the survex
R package
Python version: 3.10.5
Methods
survshap
directory contains the SurvSHAP(t) method implementation (NOTE: it can be installed as package -setup.py
)survlime.py
is the SurvLIME method implementationsurvnam
directory contains the SurvNAM method implementation (based on Jia-Xiang Chengh implementation)
Data
data_generation.R
is the code for synthetic censored data generation (for Experiments 1 and 2)data
directory contains the datasets used in experiments
Experiments
experiments
directory contains Jupyter Notebooks (*.ipynb
files) with code of the conducted experimentsresults
directory contains results of the conducted experiments
Plots
plots.R
is the code for creating Figures from the articleplots
directory contains Figures in.pdf
format