A Relational Data Mining Tool Based On Genetic Programming

In this paper, we present a Data Mining tool based on Genetic Programming which enables to analyze complex databases, involving several relation schemes. In our approach, trees represent expressions of relational algebra and they are evaluated according to the way they discriminate positive and negative examples of the target concept. Nevertheless, relational algebra expressions are strongly typed and classical genetic operators, such as mutation and crossover, have been modified to prevent from building illegal expressions. The Genetic Programming approach that we have developed has been modeled in the framework of constraints.