Phil, I can think of 2 approaches 1.) Normalize both input data streams to the same time series [may be with averaging out the changes during the difference in time stamps] and then feed it as a 1 time series. 2.) Use a hierarchical model to train 2 independent regions with the separate time series data which feeds into 1 higher level region. This should allow for the formation of independent low level representations of the data. And they may connect at a higher level region. [This will be more experimental and not much work has been done with hierarchy]
Chandan On Mon, Mar 28, 2016 at 8:13 AM, Matthew Taylor <[email protected]> wrote: > Phil, I have an example project that will converge multiple River View > data streams into one model properly with NuPIC. It is called Menorah, > check it out here: https://github.com/nupic-community/menorah > > If nothing else, it is an example of converging disparate data sources > into a multi-field model. > > --------- > Matt Taylor > OS Community Flag-Bearer > Numenta > > On Mon, Mar 28, 2016 at 7:34 AM, Phil Goddard <[email protected]> wrote: > >> Hi Marcus, >> >> >> thanks for the links, I'll take a look at them shortly. >> >> >> In terms of the hotgym example, I think of that as really being 1 time >> series input rather than multiple inputs. >> >> >> One thing I need is to be able to input multiple time series'. >> >> In particular, inputs that arrive at different time intervals. >> >> (The inputs can't be handled by aligning them with just one time vector - >> each input needs it's own time vector.) >> >> >> Thanks >> >> Phil. >> >> ------------------------------ >> *From:* nupic <[email protected]> on behalf of Marcus >> Lewis <[email protected]> >> *Sent:* Monday, 28 March 2016 5:49 AM >> *To:* [email protected] >> *Subject:* Re: Multi-input and multi-level models >> >> Hi Phil, >> >> Multiple inputs are pretty easy with the OPF (i.e. the CLAModel). For >> example, hotgym >> <https://github.com/numenta/nupic/blob/master/examples/opf/clients/hotgym/simple/model_params.py#L66> >> uses the timestamp and the current power consumption. >> >> For multi-level models, you'll probably want to use the Network API. >> Subutai gave a recent talk: https://www.youtube.com/watch?v=g9yS9zFt3dM . >> Here's a demo that uses multiple levels: >> https://github.com/numenta/nupic/blob/master/examples/network/hierarchy_network_demo.py >> >> Strictly speaking, from the Network API's perspective, the CLAModel only >> has one input, since it concatenates >> <https://github.com/numenta/nupic/blob/master/src/nupic/frameworks/opf/clamodel.py#L1108> >> the >> encodings via a MultiEncoder, but that's just an implementation detail. I >> recently created a demo that puts multiple inputs into a Network: >> https://github.com/numenta/nupic/blob/master/examples/network/core_encoders_demo.py >> >> >> Hope that helps! >> Marcus >> >> On Sun, Mar 27, 2016 at 10:06 PM, Phil Goddard <[email protected]> >> wrote: >> >>> >>> I'm looking for an example (or examples) of using NuPIC with either (or >>> both of) multiple inputs and multiple levels. >>> >>> >>> With multiple inputs, the nearest example I can find is the NY Taxi >>> example. >>> >>> However the technical paper I have indicates that the 3 inputs are >>> aggregated into one input (via competitive polling) before being fed into >>> the model. >>> >>> Can anyone tell me if it possible to have multiple inputs? >>> >>> Or do multiple inputs have to be processed into one input as per that >>> example? >>> >>> >>> I can't find the code for the NY taxi example (in the NuPIC GitHub >>> repository). >>> >>> Is it available, and if so where? >>> >>> >>> Also, is it possible to develop multi-level models? >>> >>> If anyone can point me at any technical description of such models, or a >>> code example, I'd appreciate it. >>> >>> >>> thanks >>> >>> Phil. >>> >>> >>> >>> >>> >> > -- Regards Chandan Maruthi
