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A Comparative Evaluation of Unsupervised Anomaly Detection Algorithms for Multivariate Data
Anomaly detection is the process of identifying unexpected items or events in datasets, which differ from the norm. In contrast to standard classification tasks, anomaly detection is often applied on unlabeled data, taking only the internal structure of the dataset into account. This challenge is kn...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Public Library of Science
2016
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4836738/ https://www.ncbi.nlm.nih.gov/pubmed/27093601 http://dx.doi.org/10.1371/journal.pone.0152173 |