How complex should a learner working on SEE data sets be? Our intuition is that there is a need for complex learners, if the data set has enough complexity to it, i.e. if the data set can be divided into complex and self-contained regions. On the other hand, if most of the data is noise and if the data sets can be summarized with only a small number of instances and features, then there is no need for complex learners. The updated version of the QUICK paper investigates this question. The new version with all the results/figures updated is here.