This paper proposes an inductive data mining technique (named GPR) based on genetic programming. Unlike other mining systems, the particularity of our technique is its ability to discover business rules that satisfy multiple (and possibly conflicting) decision or search criteria simultaneously. We present a step-by-step method to implement GPR, and introduce a prototype that generates production rules from real life data. We also report in this article on the use of GPR in an organization that seeks to understand how its employees make decisions in a "voluntary separation" program. Using a personnel database of 12,787 employees with 35 descriptive variables, our technique is able to discover employees' hidden decision making patterns in the form of production rules. As our approach does not require any domain specific knowledge, it can be used without any major modification in different domains.
"GPR: A Data Mining Tool Using Genetic Programming,"
Communications of the Association for Information Systems:
Vol. 5, Article 6.
Available at: http://aisel.aisnet.org/cais/vol5/iss1/6