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Weekly Report -- 22/06/2012




Developed a web-based system for performing manual classification of anomalous traffic measurements. This should greatly speed up the process of validating my anomaly detection code and will make it possible to start to crowd-source the validation in the long term.

Using my new system, I classified a new time series which had quite a few false positives. Based on this, I've concluded that my most recent threshold changes were a step in the right direction but using a fixed threshold (unsurprisingly) only works well in some instances. In response, I've started experimenting with trying to calculate a new threshold for sample mean movement that is based on the properties of the time series itself.