Surprisal-based algorithm for detecting anomalies in categorical data
Anomaly detection is an important research area in a diverse range of real-world applications. Although many algorithms have been proposed to address anomaly detection for numerical datasets, categorical and mixed datasets remain a significant challenge, primarily because a natural distance metric i...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
KeAi Communications Co. Ltd.
2025-06-01
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| Series: | Data Science and Management |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666764925000050 |
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