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predict.GBMFit() requires explicitly specifying n.trees. Would it not be a good idea to provide n.trees with a (reasonable) default value, like length(trees(object)) or the same default as in gbm::predict.gbm()? Cheers
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The value of n.trees when predicting should come from doing cross-validation. I don’t know of any other way to pick a default value. As a generally habit, I do not rely on defaults. I’d rather intentionally pick the specific values that make the most sense for the application. The (shrinkage, n.trees) combination depends a lot on the specific dataset.
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Subject: [gbm-developers/gbm3] default value for n.trees in predict() (Issue #166)
predict.GBMFit() requires explicitly specifying n.trees. Would it not be a good idea to provide n.trees with a (reasonable) default value, like length(trees(object)) or the same default as in gbm::predict.gbm()? Cheers
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predict.GBMFit()
requires explicitly specifyingn.trees
. Would it not be a good idea to providen.trees
with a (reasonable) default value, likelength(trees(object))
or the same default as ingbm::predict.gbm()
? CheersThe text was updated successfully, but these errors were encountered: