Offline Metrics:
Purpose: To validate and refine models during development before they go live.
Examples: Log Loss, AUC (Area Under the Curve) for classification problems; RMSE (Root Mean Square Error), MAPE (Mean Absolute Percentage Error) for regression and forecasting.
Advantages:
- Safer testing environment.
- No impact on real users.
- Controlled conditions.
Limitations:
- May not fully capture real-world complexities or user interactions.
Online Metrics:
Purpose: To monitor and optimize models in a live setting.
Examples: Click-through rates, conversion rates, user engagement metrics.
Advantages:
- Reflects real-time performance and user interactions.
- Allows for immediate adjustments.
Limitations:
- Riskier as poor performance affects actual users.
- Influenced by external variables.