4. The computer-implemented method of claim 3 , wherein the learning step comprises: (a) forming a projected rule for the positive class, wherein the projected rule is of substantially highest generality; (b) adding the projected rule to a set of projected rules; (c) refining each of a plurality of rules in the set of projected rules by adding one or more of a condition or a range restriction; (d) filtering to retain a predetermined number of rules in said set of projected rules; and (e) selecting a select learned rule, wherein the select learned rule is a rule having a substantially highest F-measure among rules in the set of projected rules.
3. The computer-implemented method of claim 2 , wherein the deriving step comprises: learning a learned rule; removing from the positive class training data records covered by the learned rule; and adding the learned rule to the learned rule set.