Question: What is the purpose of the term 'bias-variance tradeoff' in machine learning?

Answer: The bias-variance tradeoff represents the balance between underfitting (high bias) and overfitting (high variance) in a machine learning model. Achieving an optimal tradeoff is crucial for model generalization.

Example:

Increasing model complexity may reduce bias but increase variance, leading to overfitting.