Hi, Dear Greg,
Sorry to bother you again.
I have several questions about the 'gbm' package.
if the train.fraction is less than 1 (ie. 0.5) , then the* first* 50% will
be used to fit the model, the other 50% can be used to estimate the
performance.
if bag.fraction is 0.5, then gbm use the* random* 50% of the data to fit the
model, and the other 50% data is used to estimate the predictive
performance.
Is my understanding for train.fraction and bag.fraction right? if not,what
is the difference?
can I set both fraction=1, and only use the cross.validation to select the
iterations?
Thanks so much!
--
Sincerely,
Changbin
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