Concept Drift: What Is It and How To Address It?
What is concept drift? Concept drift is a problematic phenomenon in which a predictive model’s performance degrades over time due to changes in its environment. To illustrate, a model is trained on historical data and is used to make predictions on unseen data. This model maps the relationship between the input features and the target variable. However, over time, this learned relationship is bound to change.