Bias–variance tradeoff

Sat, 18 Jul 2026 09:48:19 +0000

Definition

The bias-variance tradeoff describes the tension between underfitting (high bias) and overfitting (high variance). High bias models make strong assumptions about data, potentially ignoring relevant relationships, while high variance models capture noise as if it were signal. In ethical AI, managing this tradeoff is crucial to ensure models generalize fairly across diverse demographic groups without perpetuating historical biases or failing in real-world deployment scenarios.

Summary

A fundamental problem in supervised learning where minimizing error requires balancing model complexity against generalization ability.

Machine Learning Theory on English AI Terms Dictionary

Bias–variance tradeoff

Definition

Summary