Rule extraction in set-valued decision information system based on evidence theory
集值信息系统中基于证据理论的规则提取

In order to improve access speed of the optimal generalized decision rules from set-valued information system, this paper use evidence theory as an effective tool in dealing with uncertainty questions. This paper discusses the application of evidence theory in set-valued information systems, defines basic probability assignment functions on similarity relation and dominance relation in set-valued information systems, proposes a new approach to extract optimal generalized decision rules based on basic probability assignment. An example is given to prove the validity of this approach and it also shows the less time complexity of this approach than other methods.