So proud that our PhD Researcher Marcin got an “Outstanding Student Paper Award” for the article entitled “Fuzzy Weighted Shapley Values based on Nearest Neighbour Classification”, which was presented at the 16th European Symposium on Computational Intelligence and Mathematics (ESCIM 2025), held in A Coruña, Spain. (ESCIM 2025 | 16th European Symposium on Computational Intelligence and Mathematics (ESCIM 2025). A Coruña (Spain), from May 18th to 21st, 2025)
Congrats, Marcin!!!
In this study, we propose a novel modification of the Exact Shapley Values based on Nearest Neighbor Classification method that incorporates fuzzy logic to better account for uncertainty in datasets. The modification introduces a fuzzy weight vector computed using the Fuzzy K-nearest neighbour algorithm, which improves the computation of Shapley values for pseudo-labeled instances. The method was validated on a real-world pilot study of 654 patients diagnosed with acute coronary syndrome. In the dataset used, one of the problems encountered in clinical practice, data uncertainty, emerged. The results show that the K-FVSNN method achieves competitive performance and maintains robust results even with up to 90%
missing labels in the training set. These results highlight the potential of K-FVSNN for handling uncertain data in medical applications. Future work will explore its application to other datasets and refine the weight vector to improve generalizability.
Many thanks to our collaborators Paweł Burchardt, Janusz Rzeźniczak and Jan Budzianowski from the Department of Cardiology, J. Struś Hospital, 61-285 Poznań, Department of Hypertension, Angiology and Internal Medicine, Poznań University of Medical Sciences, 61-848 Poznań, and Nowa Sól Multidisciplinary Hospital, 67100 Nowa Sól.
Article is available HERE.
