Anomaly Detection

[lforeman2]

A more typical use case would be to have the normal and abnormal test data mixed together as one dataset. How would one identify the anomalies (abnormal data) from the predictions of the fitted model? As it stands, the prediction is run individually on each line in test_xx_loader - and is only really useful for calculating metrics. How would you map this back to the original dataset? How would we calculate a row-wise loss or 'anomaly score' for each sequence (row) in the test data? For example, I would like to say line number 5 in the test data was an anomalous/abnormal sequence.