In machine learning, the trade-off between overfitting and generalization is effectively the trade-off between:

A. cost and benefit
B. cost and complexity
C. complexity and sample sizes

Correct Answer: B

As the flexibility (order in complexity) increases, its variance increases, and its bias decreases. So choosing the flexibility based on average test error amounts to a bias-variance trade-off.