How does polynomial regression affect bias and variance?

Updated May 15, 2026

Short answer

Increasing polynomial degree reduces bias but increases variance.

Deep explanation

Polynomial regression increases model flexibility by adding higher-degree feature transformations. Low-degree polynomials behave like linear models with high bias. High-degree polynomials fit training data closely but may oscillate heavily, leading to high variance and overfitting.

Real-world example

Modeling sales trends that fluctuate seasonally using polynomial curves.

Common mistakes

Using very high-degree polynomials without validation.

Follow-up questions

What is Runge’s phenomenon?
How do you control polynomial overfitting?

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