it is provided a method for cell anomaly detection in a network comprising receiving first training data of a first source ; receiving second training data of a second source ; generating profiles based on the first training data ; generating profiles based on the second training data ; collecting the generated profiles of the first training data and of the second training data in a pool profiles ; associating a weight with each profile in the pool of profiles ; providing a set of predictions based on the profiles and their associated weights ; and generating data for root cause diagnosis based on at least one prediction .