Dr. Krause presented our scientific results on Anomaly Detection in Univariate Time Series: An Empirical Comparison of Machine Learning Algorithms at the 19th Industrial Conference on Data Mining (www.data-mining-forum.de/) in New York. Co-autors are Mrs. Däubener (divis), Dr. Sebastian Schmitt (Honda Research Institute Europe GmbH) and Dr. Hao Wang (Universität Leiden). In this research, we use a statistical test for comparing a range of machine learning algorithms for their applicability to the task of detecting anomalies in univariate test data sets. The article can be requested by sending an email to contact@divis-gmbh.com.

Request Article