xgboost.surv-package: xgboost.surv: Extreme Gradient Boosting for Survival Analysis

In bcjaeger/xgboost.surv: Extreme Gradient Boosting for Survival Analysis

Description

Gradient boosted decision trees are an excellent machine learning algorithm to develop prediction functions. For analyses with censored outcomes, there are a number of ways to leverage the popular and efficient R package 'xgboost'. The xgboost.surv package provides a framework to help you engage with these types of risk prediction analyses using 'xgboost'.

Author(s)

Maintainer: Byron Jaeger [e-mail] (0000-0001-7399-2299)

See Also

Useful links:

• https://github.com/bcjaeger/xgboost.surv

• Report bugs at https://github.com/bcjaeger/xgboost.surv/issues

bcjaeger/xgboost.surv documentation built on Nov. 18, 2019, 6:43 a.m.