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

Published: Dec 1, 2015
Abstract
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 process data in real-time, not batches, and learn while simultaneously making predictions. There are no benchmarks to adequately test and score the efficacy...
Paper Details
Title
Evaluating Real-Time Anomaly Detection Algorithms -- The Numenta Anomaly Benchmark
Published Date
Dec 1, 2015
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