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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...
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| Publicado no: | PLoS One |
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| Main Authors: | , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Public Library of Science
2016
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4836738/ https://ncbi.nlm.nih.gov/pubmed/27093601 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0152173 |
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