Survival Analysis, Data Science, Xgboost, Hands On Tutorials, Explore.
regressions on top of the embedding produced by the underlying XGBoost model, each predicting survival at different user-defined discrete time windows. The classifiers remove individuals as they are censored, with targets that are indicators of surviving at each window. As the embedding is sparse