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stat.ML2015★ 3.5k cited
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★ 2 cited
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…