They use a random forest classifier, which is an ensemble model that gives a consensus result of several decision trees. One way to achieve this consensus is voting. Random forest models are commonly used in building chemical models like this (and in QSAR), because they are quite robust. Due to the typically small size of chemical data sets (dozens to thousands, typically), more sophisticated methods are not usable and do not perform better.