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On the evaluation of unsupervised outlier detection: measures, datasets, and an empirical study.

, , , , , , , and . Data Min. Knowl. Discov., 30 (4): 891-927 (2016)

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On the Correlation Between Local Intrinsic Dimensionality and Outlierness., , and . SISAP, volume 11223 of Lecture Notes in Computer Science, page 177-191. Springer, (2018)Introduction to Special Issue of the 9th International Conference on Similarity Search and Applications (SISAP 2016)., , and . Inf. Syst., (2019)Evaluation and Experimental Design in Data Mining and Machine Learning: Motivation and Summary of EDML 2019, , , and . (219)Data Aggregation for Hierarchical Clustering., and . Mach. Learn. under Resour. Constraints Vol. 1 (1), De Gruyter, (2022)LOSDD: Leave-Out Support Vector Data Description for Outlier Detection., , and . CoRR, (2022)Call for Special Issue Papers: Evaluation and Experimental Design in Data Mining and Machine Learning., , , and . Big Data, 8 (5): 456-457 (2020)ELKI: A large open-source library for data analysis - ELKI Release 0.7.5 "Heidelberg"., and . CoRR, (2019)HACAM: Hierarchical Agglomerative Clustering Around Medoids - and its Limitations.. LWDA, volume 2993 of CEUR Workshop Proceedings, page 191-204. CEUR-WS.org, (2021)CANDLE: Classification And Noise Detection With Local Embedding Approximations., and . LWDA, volume 2993 of CEUR Workshop Proceedings, page 219-231. CEUR-WS.org, (2021)Generalized Outlier Detection with Flexible Kernel Density Estimates., , and . SDM, page 542-550. SIAM, (2014)