Evaluate Model Performance using Appropriate Metrics and Validation Techniques

Learning Objectives

At the end of this theory note, trainees must be able to:

1. Select appropriate evaluation metrics based on the machine learning task and objective.
2. Compute and report performance metrics using scikit-learn.
3. Apply validation techniques, including cross-validation, to assess how well a model generalises.
4. Diagnose underfitting and overfitting from performance results and learning curves.
5. Document evaluation outcomes and recommend model improvement actions.