Evaluating Real-Time Anomaly Detection Algorithms -- The Numenta Anomaly Benchmark

Much of the world's data is streaming, time-series data, where anomalies give significant information in critical situations, examples abound in domains such as finance, IT, security, medical, and energy. Yet detecting anomalies in streaming data is a difficult task, requiring detectors to proc...

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Vydané v:	2015 IEEE 14th International Conference on Machine Learning and Applications (ICMLA) s. 38 - 44
Hlavní autori:	Lavin, Alexander, Ahmad, Subutai
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 01.12.2015
Predmet:	Algorithm design and analysis anomaly detection Benchmark testing benchmarks Detection algorithms Detectors Measurement Real-time systems streaming data time-series data
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