Concept Drift

Systems that classify or predict a concept (e.g., credit ratings or computer intrusion monitors) over time can suffer performance loss when the concept they are tracking changes. This is referred to as concept drift. This can either be a natural process that occurs without a reference to the system, or an active process, where others are reacting to the system (e.g., virus detection).

Use of a system outside the planned domain of application, and a common cause of performance gaps between laboratory settings and the real world.

an online supervised learning scenario when the relation between the input data and the target variable changes over time.