Decision Rules Extraction for Decision Support System with Support Vector Machine

In decision support systems, it is important to set up decision support model to assign each pattern in to different decision levels to support decision. In this paper, support vector machine-based approach is presented to build up the decision support model which can classify the patterns from multiple agents into different decision levels, so that managers make decision-making activities according to the decision level of each pattern. Experiment is conducted on real world application to investigate the feasibility of the proposed approach and the results show that the proposed approach has an effective ability to learn the decision rules.