Conformal Prediction – Machine Learning with Accuracy Guarantees

Speaker: Marharyta Aleksandrova (Faculty of Science, Technology and Medicine; University of Luxembourg)
Title: Conformal Prediction – Machine Learning with Accuracy Guarantees
Time: Wednesday, 2021.09.22, 10:00 a.m. (CET)
Place: fully virtual (contact Jakub Lengiewicz to register)
Format: 30 min. presentation + 30 min. discussion

Abstract: The property of conformal predictors to guarantee the required accuracy rate, for example 95%, makes this framework attractive in various practical applications. This property is achieved at a price of reduction in precision. In the case of conformal classification, the systems can output multiple class labels instead of one, in the case of classification – a numerical interval instead of one value. In this talk, we’ll discuss the theory behind conformal prediction and how the choice of a nonconformity function can influence the efficiency (how small the prediction set is) of the resulting classifier.