Abstract
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.
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© 1999 Springer Science+Business Media New York
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Owoc, M.L., Galant, V. (1999). Validation of Rule-Based Systems Generated by Classification Algorithms. In: Zupančič, J., Wojtkowski, W., Wojtkowski, W.G., Wrycza, S. (eds) Evolution and Challenges in System Development. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-4851-5_42
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DOI: https://doi.org/10.1007/978-1-4615-4851-5_42
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