Results of the hurdle boosted regression tree simplification procedure.

Hurdle models were fitted as a two-step process: a binomial and Poisson part. These results show that the saturated model using all spatial predictors for both binomial and Poisson parts had lower prediction deviance (e.g., Dcv) and explanatory deviance (e.g., mse) compared to hurdle models for which the binomial, Poisson or both parts were built using only the most influential spatial predictors.
Abbreviations: Dcv and SE Dcv are the mean and standard error of the 10-fold cross-validation residual deviances, Dnull and Dresid are the mean null and residual deviances, mse is the mean square error and rmpe is the relative mean prediction error.