I have a classification problem where getting true positives is much more important than true negatives.
To be clear, I know that roughly 10% of my population are actual positives, but I can assign some proportion (say 30%) of the population to be classified as positives without much cost, above all else I need to make sure that the actual positives are covered by this set.
Unfortunately the classification tools I am using in WEKA seem to be balancing precision and recall, so that it is a) not assigning as many positives as it is allowed to, and b) getting quite a bad recall value.
Is there a standard way of approaching this problem? My first guess would be to weight the cost function towards recall rather than F-score, but I don't see an easy way to do this in WEKA.