Multi-step histogram based outlier scores for unsupervised anomaly detection: ArcelorMittal engineering dataset case of study
Anomaly detection is the task of detecting samples that behave differently from the rest of the data or that include abnormal values. Unsupervised anomaly detection is the most common scenario, which implies that the algorithms cannot train with a labeled input and do not know the anomaly behavior b...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier B.V.
2023
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| Subjects: | |
| Online Access: | View Fulltext in Publisher View in Scopus |