[xeRTRex]

Auto-encoders have been more successful in fraud and anomaly detection then supervised methods. For the uninitiated: the basic concept is to reduce the feature space (i.e. the things you know) to a lower dimensional space, then decode back into the original space. When enough differences arise between the original and reconstructed variables, the event may be flagged for a human to review (or some triage process).

[amelius]

I wonder if a similar approach can be used for a classification task where one or more classes have only few training examples (those would be similar to "anomalies", I suppose).