I would like some pointers about the following problem:
I would like to detect anomalies in a pretty huge collection of railway data. Or create a baseline model for detecting future anomalies. The data I have at my disposal exists out of coordinates and speed at the given coordinate (also the time of measurement). Could this perhaps be approached as a regression problem where there's a clear(?) connection between location and speed of a train. For instance a train suddenly moving at snail's pace on a track that from historical data is considered high velocity could be a potential anomaly. If this could indeed be approached in such a way would something like SVM be an option or should I look into other algorithms?