Hello,
I am trying to model a species in biomod2 with 4 algorithms.
myBiomodModelOut_2 <- BIOMOD_Modeling(
myBiomodData_2,
models=c('GLM','GAM','ANN', 'SRE'),
NbRunEval=10,
DataSplit=70,
Yweights=NULL,
VarImport=10,
models.eval.meth=c('ROC','TSS'), # evaluation metrics will be calculated
SaveObj=TRUE,
rescal.all.models=TRUE,
do.full.models=FALSE,
modeling.id=paste(myRespName,"test", sep=""))
#building the ensemble models
myBiomodEM_2<-BIOMOD_EnsembleModeling(modeling.output=myBiomodModelOut_2,
chosen.models="all",
em.by="all",
eval.metric=c("TSS","ROC"),
eval.metric.quality.threshold=c(0.4,0.7), # all models with TSS<0.4 and
#ROC<0.7 are excluded
prob.mean=T,
prob.cv=FALSE,
prob.ci=FALSE,
prob.ci.alpha=0.05,
prob.median=FALSE,
committee.averaging=FALSE,
prob.mean.weight=FALSE,
prob.mean.weight.decay="proportional",
VarImport = 10) #calculate variable importances for ensemble models
#print variable importances for ensemble models
get_variables_importance(myBiomodEM_2)
#get evaluation scores for ensemble models
get_evaluations(myBiomodEM_2)
*However I want to project the model "GAM"*
*Error any models selected.*
### projection Present
myBiomodProj_3P <- BIOMOD_Projection(
modeling.output = myBiomodModelOut_3,
new.env = grid.present.project,
proj.name = 'current',
selected.models="all", # I have tried ------------*selected.models="GAM"*
binary.meth=c("TSS","ROC"),
compress = 'xz',
clamping.mask = F,
output.format = '.grd')
How can I do? Any sugestion?
Thanks
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