A number of analytics sytems we worked with were essentially anomaly detection. So this is close to home. In particular, that in almost all cases the systems need to be re-calibrated and re run over time.
In O'Reilly, Video:
" ... What may work for anomaly detection today may not work tomorrow. Master statistician Arun Kejariwal helps you understand why in this fascinating walk-through of modern anomaly detection systems - how the definition of “normal” changes as applications, platforms, infrastructure, and algorithms evolve; as well as recognizing the effect of context in what defines an anomaly.
Learn how you, your data, and your decision-making can keep from getting skewed in master statistician Arun Kejariwal's course from Safari on what works – and doesn't work - when building anomaly detection systems. .... "
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