Hi everyone 👋 I wanted to raise an issue we've noticed when looking at the anomaly detection algorithms code, the issue was already raised last June here. Basically, we believe that the detection period should be excluded from the training dataset. From a prediction perspective, training on the detection period can have a big impact on the anomaly score, and therefore affect the results (false positives / false negatives). Any thought ?