This process generates a decision tree on the Iris data set. Before the decision tree is generated, the input attributes are discretised so we only work on nominal attributes. We use a combination of "Select Subprocess" and "Optimize Parameters" to select the best out of five different discretizazion methods independently for each of the attributes. The process shows, that the resulting accuracy heavily depends on the choice of the method. It varies between 64% and 94%.