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I am trying to use H2O in R to run a random forest. http://docs.h2o.ai/h2oclassic/Ruser/rtutorial.html

In the documentation, I saw that there is an option for an offset parameter but I cannot find much information about how it is leveraged.

In logistic regression, I have used an offset in two ways: 1. To adjust for oversampling a binary event (http://support.sas.com/kb/22/601.html) 2. To do a two stage model where the first stage logit is calculated and then I used the logit score as an offset in the second stage so in effect the residual is modeled in stage two.

I would like to replicate both of these through random forest, if possible, but did not think it was possible until I saw the offset parameter in the H2O implementation of Random Forest. Does anyone know if the H2O offset parameter functions the same as the offset option in SAS proc logistic?

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thanks for pointing this out! The offset parameter is actually not supported for H2O's distributed random forest. The parameters will be remove in a future release. A jira ticket for the issue can be found here:https://0xdata.atlassian.net/browse/PUBDEV-5191

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