Open prabhant opened 2 years ago
I sincerely apologize for my late reply. Since in anomaly detection problems, there often exist only few labeled samples (e.g., 5 labeled anomalies) in the training set, while the labeled samples would even be reduced further in the cross-validation (CV) scenario. Some suggestions are that:
Hi,
I am a little new to Anomaly detection but I was curious about what is the right way to do cross validation while using ADBench as the test and train samples are already split via datagenerator. An easy way will be to concatenate test and train datasets and then put them in the CV loop, but is there a cleaner way possible?