3.10 Bonus track 2: Machine Learning for estimating the Cox PH model
Additionally, the new package
ranger (Wright and Ziegler 2017) is a fast implementation of the Random Forests algorithm for building ensembles of classification and regression trees, working also with survival data. Since
ranger() uses standard `Surv survival objects, it’s an ideal tool for getting acquainted with survival analysis in this machine-learning age.
Wright, Marvin N., and Andreas Ziegler. 2017. “ranger: A Fast Implementation of Random Forests for High Dimensional Data in C++ and R.” Journal of Statistical Software 77 (1): 1–17. doi:10.18637/jss.v077.i01.