Outlier detection
Outlier detection is an area of research with a long history which has applications in many fields. This article provides a nontechnical and concise overview of the commonly used approaches for detecting outliers, including classical methods, new challenges posed by real‐world massive data, and some...
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| Veröffentlicht in: | Wiley interdisciplinary reviews. Data mining and knowledge discovery 2011-05, Vol.1 (3), p.261-268 |
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| container_title | Wiley interdisciplinary reviews. Data mining and knowledge discovery |
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| creator | Su, Xiaogang Tsai, Chih-Ling |
| description | Outlier detection is an area of research with a long history which has applications in many fields. This article provides a nontechnical and concise overview of the commonly used approaches for detecting outliers, including classical methods, new challenges posed by real‐world massive data, and some of the key advances made in recent years. © 2011 John Wiley & Sons, Inc. WIREs Data Mining Knowl Discov 2011 1 261–268 DOI: 10.1002/widm.19
This article is categorized under:
Algorithmic Development > Scalable Statistical Methods
Fundamental Concepts of Data and Knowledge > Motivation and Emergence of Data Mining
Algorithmic Development > Statistics
Technologies > Structure Discovery and Clustering |
| doi_str_mv | 10.1002/widm.19 |
| format | Article |
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Algorithmic Development > Scalable Statistical Methods
Fundamental Concepts of Data and Knowledge > Motivation and Emergence of Data Mining
Algorithmic Development > Statistics
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Algorithmic Development > Scalable Statistical Methods
Fundamental Concepts of Data and Knowledge > Motivation and Emergence of Data Mining
Algorithmic Development > Statistics
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Algorithmic Development > Scalable Statistical Methods
Fundamental Concepts of Data and Knowledge > Motivation and Emergence of Data Mining
Algorithmic Development > Statistics
Technologies > Structure Discovery and Clustering</abstract><cop>Hoboken, USA</cop><pub>John Wiley & Sons, Inc</pub><doi>10.1002/widm.19</doi><tpages>8</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1942-4787 |
| ispartof | Wiley interdisciplinary reviews. Data mining and knowledge discovery, 2011-05, Vol.1 (3), p.261-268 |
| issn | 1942-4787 1942-4795 |
| language | eng |
| recordid | cdi_proquest_journals_1977745788 |
| source | Wiley Online Library Journals Frontfile Complete |
| subjects | Clustering Data analysis Data mining Outliers (statistics) Statistical methods |
| title | Outlier detection |
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