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awesome-streaming-outlier-detection

Data Outlier Detection using the Chebyshev Theorem - Brett G. Amidan, Thomas A. Ferryman, and Scott K. Cooley, 2005.** The implementation for an onine version of the algorithm using for the NAB can be found [here](https://github.com/kyrcha/NAB/blob/master/nab/detectors/chebyshev/chebyshev_detector.py). A short write-up of how the algorithm works can be read in this [blog post](http://kyrcha.info/2019/11/26/data-outlier-detection-using-the-chebyshev-theorem-paper-review-and-online-adaptation).
The Numenta Anomaly Benchmark (NAB) - NAB is a novel benchmark for evaluating algorithms for anomaly detection in streaming, real-time applications. It is composed of over 50 labeled real-world and artificial timeseries data files plus a novel scoring mechanism designed for real-time applications.

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