In this study, a first attempt at comparing and evaluating two classification tools developed within EARLINET that provide near-real-time aerosol typing information for the lidar profiles of Thessaloniki is presented. Our aim is (i) to check the performance of both supervised learning techniques in their low-resolution mode and (ii) to investigate the reasons for typing agreement and disagreement with respect to the uncertainties and the threshold criteria applied.