There is a R package called mobForest
which can fit a real random forest for count data. It is based on mod()
(model-based recursive partitioning) in the party
package. It performs Poisson regression if the family
argument is specified as poisson()
. The package is no longer in the CRAN repository, but formerly available versions can be obtained from the archive.
If you are not restricted to random forest / bagging, a boosting version is also available for count data. That is, gbm
(generalized boosted regression models). It can also fit a Poisson model.