Decision Rule Acquisition Algorithm Based on Association-Characteristic Information Granular Computing

This is a article of research which bases on the classical granular computing and the Association Rules, focus on the association rules and decision-making rules of the information system. Firstly, defines a association-rule characteristic Information Granule, which can be treated as a sub-definition of the Information Granule, and a association-rule characteristic Information Granularity matirx is defined as well. Secondly, we present a new approach of computing on support degree and confidence degree, which are commonly used in problems of association-rule and decision-rule in information systems. Finally we build a whole knowledge-obtaining algorithm for the association rules and decision-making, and test its availability by numerous experiments.