Increasing Acceptability of Decision Trees with Domain Attributes Partial Orders

There are several domains, such as health-care, in which the decision process usually has a background knowledge that must be considered. We need to maximize the accuracy of the models, but we also need them to be meaningful. Otherwise it will lead to the problem that the expert finds the obtained models incomprehensible. We propose a way for representing the knowledge of the experts in order to modify the C 4.5 algorithm to produce decision trees which are more comprehensible to medical doctors without losing accuracy.