I am modelling a claims frequency (poisson distr) in R. I am using the gbm
and xgboost
packages, but it seems that xgboost
does not have an offset parameter to take the exposure into account?
In a gbm
, one would take the exposure into account as follows:
gbm.fit(x = train,y = target, n.trees = 100,distribution = "poisson", offset = log(exposure))
How do I achieve the same with `xgboost?
PS: I cannot use the exposure as predictor since a new obs is created each time a claim is observed.
Once you have created your xgboost matrix you can set an offset using setinfo and the base_margin attribute, eg:
setinfo(xgtrain, "base_margin", log(d$exposure))
You can see the full example from the similar question I asked here: XGBoost - Poisson distribution with varying exposure / offset
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