Unfortunately I find this unconvincing
Machine learning needs realistic training data to perform a classification task, which this is - is the data presented a 'technosignature' or not. Ideally you'd like a classifier that says 'I've seen something anomalous or different to what I've seen' but that's not how classifiers work, you do need representative data for each of the classes. (Humans are really good at noticing when things are odd without representative data, ML classifiers are not). There is no representative data for a technosignature so its a complete guess if one makes it artificially. This guess is driven into the classifier.
So interesting work and a great idea for a 3rd year undergrad project where it's really more about the project than the discovery, but this isn't serious analysis of 'its aliens'!
Biting the hand that feeds IT
