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On the evaluation of unsupervised outlier detection: measures, datasets, and an empirical study, , , , , , , и . Data Mining and Knowledge Discovery, 30 (4): 891--927 (01.07.2016)A density-based algorithm for discovering clusters in large spatial databases with noise., , , , и . Kdd, 96, стр. 226--231. (1996)Biological data annotation via a human-augmenting AI-based labeling system., , , , , , , , , и 4 other автор(ы). npj Digit. Medicine, (2021)Knowledge Discovery in Databases, и . Springer-Verlag, Berlin/Heidelberg, (2000)Unsupervised Super-Resolution: Creating High-Resolution Medical Images from Low-Resolution Anisotropic Examples., , и . CoRR, (2020)Density-based clustering., , , и . WIREs Data Mining Knowl. Discov., (2020)Internal Evaluation of Unsupervised Outlier Detection., , , и . ACM Trans. Knowl. Discov. Data, 14 (4): 47:1-47:42 (2020)Incremental Clustering for Mining in a Data Warehouse Environment, , , , и . Proc. of 24th VLDB Conference, (1998)Unsupervised super-resolution: creating high-resolution medical images from low-resolution anisotropic examples., , и . Medical Imaging: Image Processing, том 11596 из SPIE Proceedings, SPIE, (2021)Potential of dissimilarity measure-based computation of protein thermal stability data for determining protein interactions., , , и . Briefings Bioinform., (мая 2023)