In theory, a QSAR model should select a subset of most significant descriptors from a large list. However, this assumes a high degree of independence between descriptors, which inevitably decreases as the list of descriptors increases. In addition, there is a distinction between fragments that directly account for a particular property and those that modulate other fragments. The QSAR models tested also includes support vector machines, which have a smaller tendency to over-fit as a classifier for small data sets .