AI & Machine Learning · Intermediate

Bias-Variance Tradeoff

The balance between error from overly simple assumptions (bias) and error from sensitivity to training data (variance).

Definition

High-bias models underfit and high-variance models overfit. Increasing model complexity typically lowers bias but raises variance. The goal is the complexity that minimizes total generalization error, often found via validation curves and regularization.

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