Stuti, RF is an ensemble approach, generating 10 trees is too less to be of
any value. Are you running in-mem version? Even in case of the distributed
version, model building time depends on your compute cluster configuration
and capacity.

Som


On Fri, Jul 11, 2014 at 4:38 AM, Suneel Marthi <suneel.mar...@gmail.com>
wrote:

> Please work off of trunk, few fixes for RDF have gone in that should
> address this issue. See release notes for details.
>
> Sent from my iPhone
>
> > On Jul 11, 2014, at 7:06 AM, Stuti Awasthi <stutiawas...@hcl.com> wrote:
> >
> > Mahout 0.7
> >
> > -----Original Message-----
> > From: Suneel Marthi [mailto:suneel.mar...@gmail.com]
> > Sent: Friday, July 11, 2014 4:29 PM
> > To: user@mahout.apache.org
> > Subject: Re: Random Forest Implementation training is too slow for 2 GB
> of data
> >
> > R u working off if trunk? Mahout version??
> >
> > Sent from my iPhone
> >
> >> On Jul 11, 2014, at 6:53 AM, Stuti Awasthi <stutiawas...@hcl.com>
> wrote:
> >>
> >> Hi all,
> >>
> >> I have some 2 GB of data and tried to  execute RF with no of trees = 10
> and maxsplitsize as 90 MB. The execution takes too much time.
> >> I have also tried with #of trees =2, then it takes less time but gives
> >> accuracy <50% If I use less data with greater no of trees , then
> >> output accuracy is >90%
> >>
> >> Is there any tuning to execute it quickly with optimal no of trees for
> accuracy > 80%.
> >>
> >>
> >> Please suggest
> >>
> >> Thanks
> >> Stuti Awasthi
> >>
> >>
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