ABSTRACT
Overtting, a problem akin to model inaccuracy, is as old as model building itself, as it is part of the modeling process. An overtted model is one that approaches reproducing the training data on which the model is built. The effect of overtting is an inaccurate model. The purpose of this chapter is to introduce a new solution, based on the data mining feature of the GenIQ Model, to the old problem of overtting. I illustrate how the GenIQ Model identies the complexity of the idiosyncrasies and subsequently instructs for deletion of the individuals that contribute to the complexity in the data under consideration.
