Unsupervised outlier detection using random subspace and subsampling ensembles of Dirichlet process mixtures

Author:

Kim Dongwook,Park JuyeonORCID,Chung Hee CheolORCID,Jeong Seonghyun

Funder

Ministry of Science, ICT and Future Planning

National Research Foundation of Korea

Yonsei University

Publisher

Elsevier BV

Reference58 articles.

1. Mean-shift outlier detection and filtering;Yang;Pattern Recognit.,2021

2. ECOD: Unsupervised outlier detection using empirical cumulative distribution functions;Li;IEEE Trans. Knowl. Data Eng.,2022

3. A. Goodge, B. Hooi, S.-K. Ng, W.S. Ng, LUNAR: Unifying local outlier detection methods via graph neural networks, in: Proceedings of the AAAI Conference on Artificial Intelligence, 2022, pp. 6737–6745.

4. Deep isolation forest for anomaly detection;Xu;IEEE Trans. Knowl. Data Eng.,2023

5. AIDA: Analytic isolation and distance-based anomaly detection algorithm;Arias;Pattern Recognit.,2023

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