3 papers
stat.ML2016
Unbiased split variable selection for random survival forests using maximally selected rank statistics
Marvin N. Wright, Theresa Dankowski, Andreas Ziegler
The most popular approach for analyzing survival data is the Cox regression model. The Cox model may, however, be misspecified, and its proportionality assumption may not always be…
stat.ML2015
ranger: A Fast Implementation of Random Forests for High Dimensional Data in C++ and R
Marvin N. Wright, Andreas Ziegler
We introduce the C++ application and R package ranger. The software is a fast implementation of random forests for high dimensional data. Ensembles of classification, regression an…
stat.ML2015
On the use of Harrell's C for clinical risk prediction via random survival forests
Matthias Schmid, Marvin Wright, Andreas Ziegler
Random survival forests (RSF) are a powerful method for risk prediction of right-censored outcomes in biomedical research. RSF use the log-rank split criterion to form an ensemble…