To compensate, one can evaluate more ligands per iteration, thereby improving the chances of selecting the strongest binders in that iteration. While this does improve the Kendall-tau correlation and the rate of discovery of strong binders in the early iterations, the benefits are negated by the increased number of randomly selected ligands evaluated to build the very first model (Fig. ).