Model Drift
Last reviewed by Moderation API
Model drift is the gradual decay in a classifier's accuracy as the language, topics, and attack patterns it sees in production diverge from the data it was trained on. Left unchecked, drift silently erodes precision and recall until the model is retrained on fresh examples.
