I'm trying to execute the Cross-Validation for the boosting regression/classification trees using the function gbm.step() from the R package dismo, but it returns a empty output and I can't figure out why. This is the code I'm using:
ColIndexCov <- match(names(myRS),colnames(DFbrt_df2))
ColIndexResp <- match(c("HasRes"),colnames(DFbrt_df2))
DFbrt_df <- DFbrt@data
DFbrt_df2 <- na.omit(DFbrt_df)
myBRT = gbm.step(data=DFbrt_df2,
gbm.x = ColIndexCov,
gbm.y = ColIndexResp,
tree.complexity = 3,
learning.rate = 10^(-8),
n.trees = 50,
family = "bernoulli",
n.folds = 4,
fold.vector = DFbrt_df2$Region.num,
step.size = 50,
verbose = F,
silent = T
)
str(DFbrt_df2)
'data.frame': 560845 obs. of 18 variables:
$ Nsamples : num 310 310 310 310 310 310 310 310 310 310 ...
$ cluster : num 39 39 39 39 39 39 39 39 39 39 ...
$ R : num 44.9 44.9 44.9 44.9 44.9 ...
$ P50 : num 0.565 0.544 0.609 0.605 0.593 ...
$ regions : Factor w/ 6 levels "China_east","China_middlesouth",..: 1 1 1 1 1 1 1 1 1 1 ...
$ HasRes : num 1 0 1 0 0 0 1 1 0 0 ...
$ use : num 10.02 9.75 0 9.38 8.77 ...
$ acc : num 0 0 0.4103 0.0769 0.0779 ...
$ tmp : num 2.46 2.46 2.46 2.46 2.45 ...
$ irg : num 1.788 0.399 1.205 1.836 1.841 ...
$ PgExt : num 3.11 0 3.7 3.11 3.18 ...
$ PgInt : num 4.69 2.76 0 3.99 2.22 ...
$ ChExt : num 3.74 0 4.33 3.74 3.81 ...
$ ChInt : num 5.01 5.99 5.35 4.88 4.97 ...
$ Ca : num 0 0 2.71 0 2.8 ...
$ veg : num 0 0 0 0 0 0 0 0 0 0 ...
$ Region.num: num 4 4 4 4 4 4 4 4 4 4 ...
$ Region : num 4 4 4 4 4 4 4 4 4 4 ...
- attr(*, "na.action")= 'omit' Named int 1 2 3 4 5 6 7 8 9 10 ...
..- attr(*, "names")= chr "1" "2" "3" "4" ...
the answer variable is the variable HasRes and the covariates are the variables use, acc, tmp, irg, PgExt, PgInt, ChExt, ChInt, ca, veg.
