Martin Tveten
Senior Research Scientist at the Norwegian Computing Center, Department of Statistics and Machine Learning. Interests: Anomaly detection, changepoint detection, sensor data.
Sessions
skchange is a python compatible framework library for detecting anomalies, changepoints in time series, and segmentation.
skchange is based on and extends sktime, the most widely used scikit-learn compatible framework library for learning with time series. Both packages are maintained under permissive license, easily extensible by anyone, and interoperable with the python data science stack.
This workshop gives a hands-on introduction to the new joint detection interface developed in skchange and sktime, for detecting point anomalies, changepoints, and segment anomalies, in unsupervised, semi-supervised, and supervised settings.