Anomaly Detection via Online Oversampling Principal Component Analysis
نویسندگان
چکیده
منابع مشابه
Anomaly Detection Using Principal Component Analysis
Anomaly detection is the identification of items, events or observations which do not conform to an expected pattern or other items in a dataset. Typically the anomalous items will translate to some kind of problem such as bank fraud, a structural defect, medical problems or finding errors in text. Anomalies are also referred to as outliers, novelties, noise, deviations and exceptions. Many tec...
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Mei-Ling Shyu1∗, Shu-Ching Chen2, Kanoksri Sarinnapakorn1, LiWu Chang3 1Department of Electrical and Computer Engineering University of Miami, Coral Gables, FL, USA [email protected], [email protected] 2Distributed Multimedia Information System Laboratory School of Computer Science, Florida International University, Miami, FL, USA [email protected] 3Center for High Assurance Computer Systems...
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ژورنال
عنوان ژورنال: IEEE Transactions on Knowledge and Data Engineering
سال: 2013
ISSN: 1041-4347
DOI: 10.1109/tkde.2012.99