Validation of Rule-based Systems Generated by Classification Algorithms

Validation of a knowledge base is an important aspect of the knowledge-based systems (KBS) development procedure, which aims to assure the system’s ability to reach correct results. Very promising seems to be knowledge-bases (KBs) generated by classification algorithms as an example of machine-learning approach. The paper addresses the issues of verification and evaluation of KBs existing as rule-based systems and generated with classification algorithms. The framework consists of three steps. The first one relies on creation a set of rules using two tested algorithms: C4.5 and GIMS and then transformation rules into decision tables. In the second one, rules are verified, taking into account two criteria: completeness and consistency. Finally, during the last step, the set of rules is evaluated using two additional criteria: adequacy and reliability. The classification problem refers to bank customers, which apply to get credit; their applications can be approved or refused. Certain unique features of generated rules are shortly commented in a summarisation.