Hi Dennis,
for associative learning you want to look at the "spatial classification",
it's on the wiki.
Btw, I would be quite interested in comparison of learning the assotiations
{A1, B1}, {A2, B2},..
with learning temporal sequences (of length 2): A1->B1->(reset to mark end
of the sequence), A2->B2->(reset).
So if you're interested in this topic, you may try both and let us know the
results please!
Cheers, Mark
On Wed, Dec 18, 2013 at 8:44 PM, Dennis Stark <[email protected]> wrote:
> I'm trying to provide prediction of one data based on other data.
>
> I.e. We observer how A and B happen in time. Then we want to predict B
> based on current A alone. I'm trying to figure if HTM is the right approach
> for associative training.
>
> On Dec 18, 2013, at 11:42 AM, Matthew Taylor <[email protected]> wrote:
>
> > I don't think feeding them interchangeably is the right approach. That
> > would spread the temporal patterns out and split them up over time,
> > and I'm not sure the CLA will do well. Are you trying to provide
> > predictions for both inputs?
> > ---------
> > Matt Taylor
> > OS Community Flag-Bearer
> > Numenta
> >
> >
> > On Wed, Dec 18, 2013 at 9:21 AM, Dennis Stark <[email protected]> wrote:
> >> I was wondering how CLA can be used with multiple sensory inputs?
> >>
> >> I.e. I have visual input and auditory input (both converted to SDRs).
> Do I feed them interchangeably if I want to for association between two
> different stimuli and use one to predict the other. OR is it more along the
> idea of HTM? Where two CLAs would merge into a third CLA? Perhaps any other
> usage scenarios exist?
> >>
> >> Dennis Stark
> >> _______________________________________________
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> >> http://lists.numenta.org/mailman/listinfo/nupic_lists.numenta.org
> >
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>
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--
Marek Otahal :o)
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