Chandan,
thanks for your thoughts. I am assuming that I'll need to use some sort of hierarchical (multi-layer) model, and have not found much info on that approach. Was hoping that someone might be able to point me towards some papers or examples. Phil. ________________________________ From: nupic <[email protected]> on behalf of Chandan Maruthi <[email protected]> Sent: Monday, 28 March 2016 3:43 PM To: [email protected] Subject: Re: Multi-input and multi-level models 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]<mailto:[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]<mailto:[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]<mailto:[email protected]>> on behalf of Marcus Lewis <[email protected]<mailto:[email protected]>> Sent: Monday, 28 March 2016 5:49 AM To: [email protected]<mailto:[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]<mailto:[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
