I have 2 datasets, one with positive instances of what I would like to detect, and one with unlabeled instances. What methods can I use ?
As an example, suppose we want to understand detect spam email based on a few structured email characteristics. We have one dataset of 10000 spam emails, and one dataset of 100000 emails for which we don't know whether they are spam or not.
How can we tackle this problem (without labeling manually any of the unlabeled data) ?
What can we do if we have additional information about the proportion of spam in the unlabeled data (i.e. what if we estimate that between 20-40% of the 100000 unlabeled emails are spam) ?