What is concept drift in deployed machine learning models?

Question

Machine Learning — Medium

What is concept drift in deployed machine learning models?

Accepted Answer

Concept drift in deployed machine learning models refers to the change in statistical properties of the target variable or the relationship between features and the target over time. This causes model performance to degrade on new data as the model's assumptions no longer hold.