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RS-Forest: A Rapid Density Estimator for Streaming Anomaly Detection
Anomaly detection in streaming data is of high interest in numerous application domains. In this paper, we propose a novel one-class semi-supervised algorithm to detect anomalies in streaming data. Underlying the algorithm is a fast and accurate density estimator implemented by multiple fully random...
Αποθηκεύτηκε σε:
| Τόπος έκδοσης: | Proc IEEE Int Conf Data Min |
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| Κύριοι συγγραφείς: | , , , , |
| Μορφή: | Artigo |
| Γλώσσα: | Inglês |
| Έκδοση: |
2014
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| Θέματα: | |
| Διαθέσιμο Online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4324726/ https://ncbi.nlm.nih.gov/pubmed/25685112 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/ICDM.2014.45 |
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