Ce metrici să folosiți pentru a evalua un nou model în timpul implementării pe un grup pilot?

Launched a new model to the pilot group, it is important to use metrics that reflect both the quality of the model and its impact on business and users. Main categories of metrics:

• Model quality:

  • For classification: accuracy, recall, precision, F1-score, ROC-AUC.
  • For regression: mean absolute error (MAE), mean squared error (MSE), R².

• Business effect metrics:

  • Conversion rate, user retention, revenue, engagement — depending on the task.

• Stability and reliability metrics:

  • Data drift, stability of predictions over time.

• User experience metrics:

  • Response time, application errors.

For pilot testing, A/B testing is often used, comparing the metrics of the new model with the current one. It is important to track not only the improvement in prediction quality but also the impact on final business indicators and user experience.