Inducing Rules for Expert System Development: An Example Using Default and Bankruptcy Data

William F. Messier, Jr. and James V. Hansen
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William F. Messier, Jr.: Fisher School of Accounting, University of Florida, Gainesville, Florida 32611
James V. Hansen: Graduate School of Management, Brigham Young University, Provo, Utah 84602

Management Science, 1988, vol. 34, issue 12, 1403-1415

Abstract: With rapidly growing interest in the development of knowledge-based computer consulting systems for various problem domains, the difficulties associated with knowledge acquisition have special importance. This paper reports on the results of experiments designed to assess the effectiveness of an inductive algorithm in discovering predictive knowledge structures in financial data. The quality of the results are evaluated by comparing them to results generated by discriminant analysis, individual judgments, and group judgments. A partial intersection of predictive attributes occurs. More importantly, for all cases tested, the inductively produced knowledge structures perform better than the competing models.

Keywords: artificial intelligence; expert systems; machine intelligence; judgment modeling (search for similar items in EconPapers)
Date: 1988
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