Hi Sebastian and Manoj,
@Manoj: What should be the value of max_nbytes parameter and will this
affect the results and time it takes to run cross_validation, grid_search
etc?
Thanks
Kindest Regards
Waseem
On Fri, Feb 12, 2016 at 4:42 PM, Sebastian Raschka <se.rasc...@gmail.com>
wrote:
> Hi, Waseem,
> I think lowering the value of n_jobs would help; as far as I know, each
> process get a copy of the data? Just stumbled upon spark-sklearn a few days
> ago, maybe that could help as well:
>
>
> https://databricks.com/blog/2016/02/08/auto-scaling-scikit-learn-with-spark.html
>
> When I understand correctly, the data is still copied, but here, each node
> gets a copy instead of one machine with many copies.
>
>
>
>
> > On Feb 12, 2016, at 11:35 AM, muhammad waseem <m.waseem.ah...@gmail.com>
> wrote:
> >
> > Hi,
> >
> > I am trying to fit my model using regression trees but the problem is,
> it consumes a lot of RAM, which makes my code unresponsive. By looking at
> different forums and platforms, I think this is a common problem. I was
> wondering, how you free up memory or what are the best ways to run the
> fitting process/cross-validation without running out of memory? This
> problem is mostly with all regression trees (I think with other ML
> algorithms as well). Shall I try to run without n_job=-1 and use some other
> value (e.g. n_jobs=10) in cross_validation?
> >
> > Thanks
> > Kindest Regards
> > Waseem
> >
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