Concept
What is the bias-variance tradeoff?
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Answer
Total error = Bias² + Variance + Irreducible Noise. Bias: error from wrong assumptions (underfitting — too simple model). Variance: error from sensitivity to training data (overfitting — too complex model). Reducing one often increases the other. Sweet spot via regularization, ensemble methods, and proper model complexity.