Model Performance Gap Trend 2026

A model performance gap refers to the discrepancy between a machine learning model's accuracy in training versus real-world deployment. It is used to diagnose overfitting, bias, or data drift. Data scientists and ML engineers benefit by refining models, improving generalization, and ensuring reliable predictions in production environments.