Sure. I have two inputs from different sensors. Having a sequence from the first sensor (which isn't of a fixed size), I want to predict a sequence from the second sensor (which right now is of a fixed size of two, but it would be nice to generalize to non-fixed size later). When a sequence from the first sensor is passed to Nupic and it returns a prediction, another sequence from the first sensor is then passed, that have no relation whatsoever with the previous sequence. That's what I meant with non-streaming data. Each sequence is independent from the other.
On Wed, Jan 6, 2016 at 2:04 PM, Matthew Taylor <[email protected]> wrote: > Hi Sebastian, > > We recommend you use the swarming library to identify the best SP and TM > parameters. See https://github.com/numenta/nupic/wiki/Running-Swarms for > details. > > I'm not sure what you mean by non-streaming data, can you elaborate? > > > --------- > Matt Taylor > OS Community Flag-Bearer > Numenta > > On Tue, Jan 5, 2016 at 3:42 PM, Sebastián Narváez <[email protected]> > wrote: > >> Hey guys. Is there any recommendations for the SP and TM parameteres >> based on the type of inputs or the encoder used? Also, how does swarming >> behave with non-streming data? (i.e.: A dataset of independent sequences). >> >> Thanks in advance! >> > >
