A typical data mining project seeks to answer questions such as “which prospects will respond to offer X?” “which credit applicants will repay their loans?” or “who will defect to the competition?” on the basis of databases with examples of previous interactions. But often the resulting models do not perform optimally. For this reason, data mining practitioners turn to methods such as ROC curves to assess their models. This project aims to develop optimisation methods for machine learning approaches such as SVMs that do allow for this.