Comparison of spatial and non-spatial tuning

fo <- slides ~ dem + slope + hcurv + vcurv + log.carea + cslope

Spatial tuning

sp_tuning <- sptune_rf(fo, ecuador, nfold = 5, step_factor = 1,
                       rf_fun = "rfsrc", partition_fun = "partition_kmeans")

Partitioning method: 'partition_kmeans'.
'step_factor' must be > 1; setting to '2'.
Using 'foreach' parallel mode with 4 cores on 54 combinations.
Unique 'ntrees': 9. Unique 'mtry': 6.

plot_hyper_rf(sp_tuning)

non-spatial tuning

non_sp_tuning <- sptune_rf(fo, ecuador, nfold = 5,
                           rf_fun = "rfsrc", partition_fun = "partition_cv")

Spatial cross-validation

sp_tuning_spcv <- sperrorest(fo, ecuador, 
                             smp_fun = partition_kmeans, 
                             smp_args = list(repetition = 100, nfold = 5),
                             pred_args = list(probabilities = TRUE),
                             par_args = list(par_mode = "apply", par_units = 25))