Warning: Some posts on this platform may contain adult material intended for mature audiences only. Viewer discretion is advised. By clicking ‘Continue’, you confirm that you are 18 years or older and consent to viewing explicit content.
#2 seems to require #3 by definition – the model can’t know what spam is without knowing what ham is as well. In general a DSpam model would seem to be the right one – all posts used to train ham, individual posts marked as spam are removed from the ham set and added to the spam set, and then a separate spam feed that could be monitored for false positives.
In general all of these approaches sound fine to me – I hope that mastodon can develop a built-in spam suppression system but for now we have to rely on these bespoke approaches.
#2 seems to require #3 by definition – the model can’t know what spam is without knowing what ham is as well. In general a DSpam model would seem to be the right one – all posts used to train ham, individual posts marked as spam are removed from the ham set and added to the spam set, and then a separate spam feed that could be monitored for false positives.
In general all of these approaches sound fine to me – I hope that mastodon can develop a built-in spam suppression system but for now we have to rely on these bespoke approaches.