Dear gbm users,
When running predict.gbm() on a "large" dataset (150,000 rows, 300 columns,
500 trees), I notice that the memory used by R grows beyond reasonable
limits. My 14GB of RAM are often not sufficient. I am interpreting this as a
memory leak since there should be no reason to expand memory needs once the
data are loaded and passed to predict.gbm() ?
Running R version 2.9.2 on Linux, gbm package 1.6-3.
Thanks,
Markus
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