Detecting Concept Drift in Deployed Machine Learning Models: How well do Margin Density-based concept drift detectors identify concept drift in case of synthetic/real-world data?

When deployed in production, machine learning models sometimes lose accuracy over time due to a change in the distribution of the incoming data, which results in the model not reflecting reality any longer. A concept drift is this loss of accuracy over time. Drift detectors are algorithms used to detect such drifts. Drift detectors are important...