A big-stepped probability approach for discovering default rules
Résumé
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". The rules which are learnt are genuine default rules, which could be used (under some conditions) in a non-monotonic reasoning system, which can be encoded in possibilistic logic. Keywords: knowledge discovering, default rules, non-monotonic reasoning, big steppedprobabilities.