The bias-variance trade-off describes the relationship between model complexity and performance.
- High bias (underfitting) occurs when a model is too simple, leading to poor performance on both training and test data.
- High variance (overfitting) happens when a model is overly complex, performing well on training data but poorly on unseen data.
Ways to Reduce Bias and Variance:
Related to Overfitting