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This readme is a brief overview and contains details for setting up NAB. Please
refer to the following for more details about NAB scoring, data, and motivation:

- [Evaluating Real-time Anomaly Detection Algorithms](http://arxiv.org/abs/1510.03336) - Original publication of NAB
- [Unsupervised real-time anomaly detection for streaming data](http://www.sciencedirect.com/science/article/pii/S0925231217309864) - covers NAB and Numenta's HTM-based anomaly detection algorithm
- [Unsupervised real-time anomaly detection for streaming data](http://www.sciencedirect.com/science/article/pii/S0925231217309864) - The main paper, covering NAB and Numenta's HTM-based anomaly detection algorithm
- [NAB Whitepaper](https://github.com/numenta/NAB/wiki#nab-whitepaper)
- [Evaluating Real-time Anomaly Detection Algorithms](http://arxiv.org/abs/1510.03336) - Original publication of NAB

We encourage you to publish your results on running NAB, and share them with us at [nab@numenta.org](nab@numenta.org). Please cite the following publication when referring to NAB:

Lavin, Alexander and Ahmad, Subutai. *"Evaluating Real-time Anomaly Detection
Algorithms – the Numenta Anomaly Benchmark"*, Fourteenth International
Conference on Machine Learning and Applications, December 2015.
[[PDF]](http://arxiv.org/abs/1510.03336)
Ahmad, S., Lavin, A., Purdy, S., & Agha, Z. (2017). Unsupervised real-time
anomaly detection for streaming data. Neurocomputing, Available online 2 June
2017, ISSN 0925-2312, https://doi.org/10.1016/j.neucom.2017.04.070

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