Adaptive Bernstein change detector for high-dimensional data streams
Marco Heyden,
Edouard Fouché,
Vadim Arzamasov
et al.
Abstract:Change detection is of fundamental importance when analyzing data streams. Detecting changes both quickly and accurately enables monitoring and prediction systems to react, e.g., by issuing an alarm or by updating a learning algorithm. However, detecting changes is challenging when observations are high-dimensional. In high-dimensional data, change detectors should not only be able to identify when changes happen, but also in which subspace they occur. Ideally, one should also quantify how severe they are. Our… Show more
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