Accelerated and interpretable oblique random survival forests. (arXiv:2208.01129v1 [stat.ME])

The oblique random survival forest (RSF) is an ensemble supervised learning
method for right-censored outcomes. Trees in the oblique RSF are grown using
linear combinations of predictors to create branches, whereas in the standard
RSF, a single predictor is used. Oblique RSF ensembles often have higher
prediction accuracy than standard RSF ensembles. However, assessing all
possible linear combinations of predictors induces significant computational
overhead that limits applications to large-scale data sets. In addition, few
methods have been developed for interpretation …

arxiv random survival