Real-Time Anomaly Detection in Time Series Data Streams

Description The research goal of my master thesis was to find real-time capable solutions to automatically detect anomalies in time series data streams, which are especially useful to monitor servers. I evaluated several algorithms and finally ensembled an own algorithm which meets almost all of the previously gathered requirements. In the figure, you can see a collection of outliers, the algorithm is so good, it is even hard to see the anomaly behind all the true positives (green dots) ;-) At the beginning of the measurements, there are two false positives (red dots) [Read More]