Concept drift vs data drift vs covariate drift

Do you always get confused among concept drift vs data drift vs covariate drift like me?

The diagram (from a research paper, provides a clear illustration of the different terms.

In summary, concept drift in data refers to changes in environmental conditions that differ from the original environmental conditions under which a model is trained.

Concept drifts can involve both changes in distributions or in relationships between the variables.

When concept drift occurs, it can lead to a degradation of a model’s predictive performance over time, which then requires the model to be retrained to learn from the new environment.

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