Affiliations: Department of Medical Informatics, Shimane University,
School of Medicine, 89-1 Enya-cho Izumo City, Shimane 693-8501, Japan
Abstract: One of the most important problems with rule induction methods is
that they cannot extract rules, which plausibly represent expert decision
processes. In this paper, the characteristics of experts' rules are closely
examined and a new approach to extract plausible rules is introduced, which
consists of the following three procedures. First, the characterization of
decision attributes (given classes) is extracted from databases and the concept
hierarchy for given classes is calculated. Second, based on the hierarchy,
rules for each hierarchical level are induced from data. Then, for each given
class, rules for all the hierarchical levels are integrated into one rule. The
proposed method was evaluated on a medical database, the experimental results
of which show that induced rules correctly represent experts' decision
processes.
