Business Rule Learning with Interactive Selection of Association Rules
Today, there is an increasing demand for Decision Support Systems (DSS). The penetration of DSS solutions to many domains is stifled by the fact that building a DSS requires a significant amount of time from users, who need to be not only domain experts, but also skilled knowledge engineers. This paper presents the implementation of a classification system based on learning of association rules in conjunction with Drools rule engine. The rules are interactively discovered with a web-based data mining system EasyMiner.eu. The rules are approved and edited by the domain expert before they are deployed for classification.