Development of Methods How to Avoid the Overfitting-Effect within the GeLog-System

This article examines the methods how to avoid an overfitting-effect within GeLog-systems. This effect can be observed in nearly all systems of inductive concept learning, if due to false classification of examples false, especially too specific theories, are learned. There are a number or procedures, how to counter the eects of the overfitting-effect or to avoid it. This article develops criteria for the selection of those procedures. In this context, the integrability into the GeLog-system , a system of genetic inductive logic programming, is of great importance. Finally