Since real-world decision making include several decision steps, real-world decision making agents have several sophisticated diagnostic reasoning mechanisms. Thus, if we want to update these reasoning steps, we have to extract rules for each step from real-world datasets. However, one of the most important problems on rule induction methods is that they aim at induction of simple rules and can...

Numerous studies on bankruptcy prediction have widely applied data mining techniques to finding out the useful knowledge automatically from financial databases, while few studies have proposed qualitative data mining approaches capable of eliciting and representing experts’ problem-solving knowledge from experts’ qualitative decisions. In an actual risk assessment process, the discovery of bank...

OBJECTIVES The aim was to evaluate the potential for monotonicity constraints to bias machine learning systems to learn rules that were both accurate and meaningful. METHODS Two data sets, taken from problems as diverse as screening for dementia and assessing the risk of mental retardation, were collected and a rule learning system, with and without monotonicity constraints, was run on each. ...