Aside from the user experience aspect, this sort of feedback would be very useful for developing receiver operating characteristic curves (ROC) where the false

Aside from the user experience aspect, this sort of feedback would be very useful for developing receiver operating characteristic curves (ROC) where the false positive rate is plotted against the true positive rate--it's what I use to judge the performance of all my machine learning algorithms. I have the highest respect for Flightcaster and what they are trying to do, but their business is tricky. Users are expecting truth but their product is inherently untruthful--meaning that there is always going to be uncertainty. Leaving this out in their marketing can be quite dangerous (to their business) as you have shown. My question to FC: have you considered far simpler algorithms to do the types of things you're trying to do? Is there marked performance gain from using more complex techniques? In my experience, using more complex algorithms can sometimes yield better results, but the added complexity is prohibitive when exploring exactly why an algorithm made a certain prediction.