Yes, I think the second link is a test build of a parallelized cv loop within
gbm().
On Mar 24, 2013, at 9:28 AM, "Lorenzo Isella" wrote:
> Thanks a lot for the quick answer.
> However, from what I see, the parallelization affects only the
> cross-validation part in the gbm interface (but it
Thanks a lot for the quick answer.
However, from what I see, the parallelization affects only the
cross-validation part in the gbm interface (but it changes nothing when
you call gbm.fit).
Am I missing anything here?
Is there any fundamental reason why gbm.fit cannot be parallelized?
Lorenzo
See this:
https://code.google.com/p/gradientboostedmodels/issues/detail?id=3
and this:
https://code.google.com/p/gradientboostedmodels/source/browse/?name=parallel
Max
On Sun, Mar 24, 2013 at 7:31 AM, Lorenzo Isella wrote:
> Dear All,
> I am far from being a guru about parallel programm
Dear All,
I am far from being a guru about parallel programming.
Most of the time, I rely or randomForest for data mining large datasets.
I would like to give a try also to the gradient boosted methods in GBM,
but I have a need for parallelization.
I normally rely on gbm.fit for speed reasons, a
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