Formalization and Induction of Medical Expert System Rules Based on Rough Set Theory
Shusaku Tsumoto · Studies in fuzziness and soft computing · 1998
One of the most important problems in developing expert systems is knowledge acquisition from experts[BS1]. In order to automate this problem, many inductive learning methods, such as induction of decision trees[BF1, QU1], rule induction methods[MI1, MI2, QU1] and rough set theory[PA1, ZI1], are introduced and applied to extract knowledge from databases, and the results show that these methods are appropriate. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.