Matt,

Thanks for your kind help, and looking forward to reading your tutorial.

Regards,
Richard

On Thu, May 14, 2015 at 11:45 PM, Matthew Taylor <[email protected]> wrote:

> Whether you need to swarm on each field of data depends on whether the
> columns of data have different characteristics. If they are all
> basically within the same bounds, same data type, etc., you generally
> won't need to swarm against all of them and you can just reuse the
> model params from one swarm against a field for each column. But if
> they are different types and have drastically different parameters,
> you should swarm against them all.
>
> Since so many of you are asking about this, I guess I should put some
> time into finishing the "Multiple Hot Gyms Prediction Tutorial"
> (https://github.com/numenta/nupic/issues/1320), which would give
> examples of running an ensemble of models against many input fields. I
> started it at
> https://github.com/rhyolight/nupic/tree/many-hot-gyms-prediction
> but it is quite out-of-date at this point.
> ---------
> Matt Taylor
> OS Community Flag-Bearer
> Numenta
>
>
> On Thu, May 14, 2015 at 12:51 AM, email email <[email protected]>
> wrote:
> > Hi, Matt,
> >
> > I also have the same case as Tom. My question is if I create several
> models,
> > do I need to write the separate swarm description and swarm.py files for
> > each model and run swarm one by one? If not, how to integrate the swarm
> > description and swarm files, or swarm with several description configs
> in a
> > parallel form?
> >
> > Thanks
> >
> > Regards,
> > Richard
> >
> > On Thu, May 7, 2015 at 11:29 PM, Matthew Taylor <[email protected]>
> wrote:
> >>
> >> Tom,
> >>
> >> This is something we'd like to do, but doesn't work yet.
> >>
> >> https://github.com/numenta/nupic/issues/1712.
> >>
> >> Your only option at this point (and it's not a horrible option) is to
> >> create several models for the same input, one for each field you'd
> >> like to predict. Then send them all the input rows at the same time
> >> while they predict for their own fields.
> >>
> >> Regards,
> >> ---------
> >> Matt Taylor
> >> OS Community Flag-Bearer
> >> Numenta
> >>
> >>
> >> On Thu, May 7, 2015 at 12:01 AM, Tom Tan <[email protected]> wrote:
> >> > Hi,
> >> >
> >> > Is there an example or documentation how to predict multiple fields?
> I
> >> > looked at the example using multiple fields
> >> > https://github.com/subutai/nupic.subutai/tree/master/swarm_examples,
> and
> >> > it
> >> > is to use multiple field inputs to predict a single output.   Let’s
> say
> >> > I
> >> > have a stream of CPU, RAM, I/O, and network data for a server.   I’d
> >> > like to
> >> > CLA model to be able to predict next time period CPU, Ram, I/O and
> >> > network
> >> > values at once, and perhaps generate one anomaly score considering all
> >> > predictions vs. actual.   Do I have to use multiple models, one for
> each
> >> > data field to accomplish this?
> >> >
> >> > Regards,
> >> > Tom
> >> >
> >> >
> >> >
> >>
> >
>
>

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