I have a database of multivariate time series that I want to cluster in order to find natural grouping of features. I am thinking of taking each cluster points and perform an ARIMA analysis on its points. Within those clusters, what should be the best way to infer those groupings in the original mutltidimentional feature space? a sample of my time series is :
TimeStamp | Sensor0 | Sensor1| Sensor2 2015-02-05 11:30|<Min | On | off 2015-02-05 11:31|<Min | on | off 2015-02-05 11:32| Action2 | 10 | 0.0001 2015-02-07 11:33| Action2 | 10 | 0.00012 2015-02-07 11:34| Action2 | 10 | 0.00012 2015-02-07 11:35| Action2 | 20 | 0.00015
I have roughly 10 separate groupings and I don't think performing different ARIMA calculations would be the best efficient method. Any thoughts or ideas are also welcome!