On Fri, 10-Jul-2009 at 09:41AM -0700, Michael wrote:
|> Here is my code:
|> mygbm<-gbm.fit(y=mytraindata[, 1], x=mytraindata[, -1],
|> interaction.depth=4, shrinkage=0.001, n.trees=20000, bag.fraction=1,
|> distribution="bernoulli")
|>
|> Here is the error:
|> Error in gbm.fit(y = mytraindata[, 1], x = mytraindata[, -1],
|> interaction.depth = 4, :
|> The dataset size is too small or subsampling rate is too large:
|> cRows*train.fraction*bag.fraction <= n.minobsinnode
|>
|> What might be the problem?
Well, it tells you:
cRows*train.fraction*bag.fraction <= n.minobsinnode
You don't tell us anything about what you have and what you're trying
to do, so I couldn't possibly say more.
--
~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.
___ Patrick Connolly
{~._.~} Great minds discuss ideas
_( Y )_ Average minds discuss events
(:_~*~_:) Small minds discuss people
(_)-(_) ..... Eleanor Roosevelt
~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.