Can the Anomaly Detection be trained at a sampling rate and opertionalized at a different one?
Hi community,
Can the Anomaly Detection functionality be trained at a sampling rate and opertionalized at a different sampling rate?
Use case:
Let's say I have a dataset that has 144 records from an asset that has been sampled at sampling rate of 10 minutes (doing the math that is one day of data).
Since the only way to train the model behind the Anomaly Detection functionality is through streaming data, I would have to run a simulation to train the model. Knowing that once the model is trained it will be migrated to the production environment where the sampling rate is 10 minutes, do I have to run a one day long simulation or could I speed up the process by reducing the simulation/training sampling rate?

