Sebastian, is it possible to talk about this data without abstraction? I'm having a hard time understanding what you mean by "fixed size sequence". It would help if you could talk about the actual sensors producing this data?
Either way, if you swarm for a model with two data sources in an attempt to optimize the predictions of one of these fields, many times the swarm exposes an unexpected lack of correlation between the two fields. Sometimes it is simply that to predict field A, the value of field B simply does not matter enough to keep track of it. If both sequences are independent of each other like you say, I would not expect the value of one field to affect the value of another field at all. --------- Matt Taylor OS Community Flag-Bearer Numenta On Fri, Jan 8, 2016 at 7:26 PM, Sebastián Narváez <[email protected]> wrote: > 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! >>> >> >> >
