Zvika, Before you try a different encoder, you should attempt to use the CoordinateEncoder directly. It can accept X,Y coordinates and a "radius" which can represent speed. That is what I used to get NuPIC to do anomaly detection on Minecraft XYZ coordinates: https://github.com/nupic-community/mine-hack/blob/master/python/nupic_client.py#L71-L79
And for an anomaly detection model on coordinates, you won't need to swarm because we already have model params that work well detection these types of anomalies here: https://github.com/nupic-community/mine-hack/blob/master/python/model_params/model_params.py. You should be able to re-use those model params (maybe with a few string replacements). --------- Matt Taylor OS Community Flag-Bearer Numenta On Mon, Oct 19, 2015 at 5:05 AM, Zvika Ashani <[email protected]> wrote: > Hi Nupic, > > I am trying to see if I can do anomaly detection over a data set that > represents object tracks. Each object track is a list of data points that > have the following information: > > - timestamp > - position (x,y between 0 and 1) > - speed > > I want to learn a large number for such tracks and then look for anomalies in > new tracks. > This is kind of like the nupic.geospatial example but the position data is in > a different coordinate system. > I am looking at using a vector encoder with each sample being [x,y,speed] and > then feeding each track as a separate sequence into the model. > > Questions: > > - is this the correct approach or is there some better way of encoding the > data? > - is it possible to swarm over this to find the best model? > > Thanks, > Zvika
