Optimised probabilistic active learning (OPAL)

by Georg Krempl, Daniel Kottke, Vincent Lemaire. In contrast to ever increasing volumes of automatically generated data, human annotation capacities remain limited. Thus, fast active learning approaches that allow the efficient allocation of annotation efforts gain in importance. Furthermore, cost-sensitive applications such as fraud detection pose the additional challenge of differing misclassification costs between classes. […]

Read More