Learned from DMC: Crossvalidation is important Rarely found in Anomaly Detection, why? A bit more complicated (not all samples are equal), but no reason why not ->So I implemented it into yano folding only on normal data How to handle anomalies? If not folding them, cross-validation less useful if folding them, often rare anomalies even more rare ->test set always 50\% anomalous ->Also improves simple evaluation metrics (accuracy) Do you know a reason why Cross Validation is not common in AD? Are there Problems with the way I fold my Anomalies?