The default shrinkage (learning rate) for mboost is much higher than for gbm.
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I'm attempting to fit boosted regression trees to a censored response using
IPCW weighting. I've implemented this through two libraries, mboost and
gbm, which I believe should yield models that would perform comparably.
This, however, is not the case - mboost performs much better. This seems
odd
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