Abstract
Belief rule-based (BRB) systems are usually regarded as much more interpretable than those systems based on black-box techniques. Unfortunately, understanding the reasoning behavior of BRB systems is a complex task, although the use of linguistic variables and rules makes BRB systems have outstanding semantic expressiveness. In this study, a rule reasoning diagram, named RULING, is proposed as a tool for visual representation and exploratory analysis of the BRB systems. RULING describes the BRB system in the form of a network graph based on the interaction between the rules, which allows users to understand the behavior of the BRB system by examining the information represented graphically, and provides an effective means to improve the interpretability of BRB systems. In the meanwhile, some quantitative indicators based on the network structure and rule characteristics are proposed to evaluate the performance of rules and BRB systems. A classification case and a regression case are studied as examples to illustrate the feasibility and effectiveness of RULING. The results indicate that RULING can offer many possibilities for BRB system analysis and evaluation, such as identifying important rules, interpreting rule interactions, detecting inconsistent rules, and guiding the adjustment of the rule base.
Published Version
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