Model Evaluation and Validation
- Measuring model performance (R², MSE, MAE)
- Training and testing data splits
- MicroSim: Cross-validation simulation
- Understanding overfitting and underfitting
- Bias-variance trade-off
- Model selection criteria
- Performance metrics for different problem types