Training vs Validation Error Curves¶
Description¶
Visualize how training and validation errors evolve during model training.
Learning Objectives¶
- Understand the relationship between training and validation error
- Recognize signs of overfitting and underfitting
- Identify optimal early stopping points
Key Scenarios¶
- Good Fit: Both errors decrease and converge
- Overfitting: Training error decreases, validation error increases
- Underfitting: Both errors remain high
- Early Stopping: Optimal point before overfitting begins