Do you always get confused among concept drift vs data drift vs covariate drift like me?
The diagram (from a research paper, https://arxiv.org/abs/1511.03816) 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.