A BIG-STEPPED PROBABILITY APPROACH FOR DISCOVERING DEFAULT RULES
Salem Benferhat, Didier Dubois, Sylvain Lagrue, Henri M. Prade · International Journal of Uncertainty Fuzziness and Knowledge-Based Systems · 2003
This paper deals with the extraction of default rules from a database of examples. The proposed approach is based on a special kind of probability distributions, called "big-stepped probabilities", which are known to provide a semantics for non-monotonic reasoning. The rules which are learnt are genuine default rules, which could be used (under some conditions) in a non-monotonic reasoning system and can be encoded in possibilistic logic.