Guess-And-Verify Heuristics for Reducing Uncertainties in Expert
  Classification Systems
  An expert classification system having statistical information about the
prior probabilities of the different classes should be able to use this
knowledge to reduce the amount of additional information that it must collect,
e.g., through questions, in order to make a correct classification. This paper
examines how best to use such prior information and additional
information-collection opportunities to reduce uncertainty about the class to
which a case belongs, thus minimizing the average cost or effort required to
correctly classify new cases.
