With the boom of machine learning, anomaly detection methods are gaining traction as a tool to test at the LHC the ample variety of new physics models proposed up to date, and those still not imagined. SOFIE is a novel concept in anomaly detection, joining the best features of supervised methods with the model independence of unsupervised ones, whose performance largely improves over purely unsupervised tools .