Hello NuPIC, I have been working on a new River View feature [1] and thinking of putting together another example HTM application (for NuPIC) that uses more than one scalar input field to make a multistep prediction. For example, it is pretty obvious if you look into this aggregated data [2] that an event occurred in early August that caused many people to call the city of Chicago to request tree debris removal. This should correlate directly with existing Chicago wind speed and precipitation data [3] (spoiler: it was a tornado [4]).
Would something like this be an informative sample application? One that shows how to swarm over multiple input fields to find those that contribute to the best prediction of another field using live streaming data from River View? Please speak up if you are interested, especially if you think you might want to do something like this for your HTM Challenge submission. ;) [1] https://github.com/numenta/nupic/wiki/River-View-and-HTM#aggregated-geospatial-data [2] http://data.numenta.org/chicago-311/Tree%20Debris/data.html?aggregate=1%20day&since=1435854390 [3] http://data.numenta.org/chicago-beach-weather/Foster%20Weather%20Station/data.html?limit=5000 [4] http://www.weather.gov/lot/2August2015 Regards, --------- Matt Taylor OS Community Flag-Bearer Numenta
