I am having a strange problem. I have successfully ran this code on my laptop, but when I try to run it on another machine first I get this warning
Distribution not specified, assuming bernoulli ..., which I expect but then I get this error:
Error in object$var.levels[[i]] : subscript out of bounds
library(gbm)
gbm.tmp <- gbm(subxy$presence ~ btyme + stsmi + styma + bathy,
data=subxy,
var.monotone=rep(0, length= 4), n.trees=2000, interaction.depth=3,
n.minobsinnode=10, shrinkage=0.01, bag.fraction=0.5, train.fraction=1,
verbose=F, cv.folds=10)
Can anybody help? The data structures are exactly the same, same code, same R. I am not even using a subscript here.
EDIT: traceback()
6: predict.gbm(model, newdata = my.data, n.trees = best.iter.cv)
5: predict(model, newdata = my.data, n.trees = best.iter.cv)
4: predict(model, newdata = my.data, n.trees = best.iter.cv)
3: gbmCrossValPredictions(cv.models, cv.folds, cv.group, best.iter.cv,
distribution, data[i.train, ], y)
2: gbmCrossVal(cv.folds, nTrain, n.cores, class.stratify.cv, data,
x, y, offset, distribution, w, var.monotone, n.trees, interaction.depth,
n.minobsinnode, shrinkage, bag.fraction, var.names, response.name,
group)
1: gbm(subxy$presence ~ btyme + stsmi + styma + bathy, data = subxy,var.monotone = rep(0, length = 4), n.trees = 2000, interaction.depth = 3, n.minobsinnode = 10, shrinkage = 0.01, bag.fraction = 0.5, train.fraction = 1, verbose = F, cv.folds = 10)
Could it have something to do because I moved the saved R workspace to another machine?
EDIT 2: ok so I have updated the gbm package on the machine where the code was working and now I get the same error. So at this point I am thinking that the older gbm package did perhaps not have this check in place or that the newer version has some problem. I don't understand gbm well enough to say.