Some (stock market) traders have the ability to produce a high percentage of winning trades (80%+, positive return) over years. I had the chance to look into real money trades of two such traders and I also got trading instructions from them for research.
Now the interesting part is that if you strictly follow their rules then you usually end up with more losers than winners on the long run. But after a while you get some kind of subconscious "feeling" for winners which also shows in the results. I assume that this "feeling" is a hidden function which can be modeled.
My question is: Is there work about how to model such "gut feeling" and subconscious knowledge by means of machine learning (especially with little training data sets)? Is there relevant literature about this topic?