Unpacking the black box: LIME and SHAP with extreme gradient boosting in precision medicine

XGboostML_LIME: Integrating LIME into the XGBoostML framework
XGboostML_SHAP: Integrating SHAP into the XGBoostML framework

Overview

XGboostML is XGBoost with modified loss function for prediction of ITR.

Ensure you have the following installed:

Name		Name	Last commit message	Last commit date
Latest commit History 3 Commits
README.md		README.md
XGboostML_lime_shao_binary.ipynb		XGboostML_lime_shao_binary.ipynb
XGboostML_lime_shao_continuous.ipynb		XGboostML_lime_shao_continuous.ipynb
XGboostML_lime_shao_time_to_event.ipynb		XGboostML_lime_shao_time_to_event.ipynb
simulation_beta1.csv		simulation_beta1.csv
simulation_beta2.csv		simulation_beta2.csv
simulation_beta3.csv		simulation_beta3.csv