2021/07/04 by Vladimir Vovk, Vovk, Vladimir, Ivan Petej +3
Computer Science · #60G25 #60G42 #62F03 #62M20 (Secondary) #68Q32 (Primary) 68T05 #Anomaly Detection Techniques and Applications #Data Stream Mining Techniques #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and Data Classification
paper · pdf · doi:10.48550/arxiv.2107.01726
openalex publication_date 2021/07/04 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
This paper proposes a way of protecting probabilistic prediction models against changes in the data distribution, concentrating on the case of classification and paying particular attention to binary classification. This is important in applications of machine learning, where the quality of a trained prediction algorithm may drop significantly in the process of its exploitation. Our techniques are based on recent work on conformal test martingales and older work on prediction with expert advice, namely tracking the best expert.