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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