What is the bias-variance tradeoff in large-scale AI systems?
Reviewed by Jason Burns, Editorial Steward · Last updated
The bias–variance tradeoff describes the tension between models that are too simple (high bias, underfitting the data) and models that are too complex (high variance, overfitting to noise); the goal is a model complexity that minimizes total error on unseen data.