Explain how overfitting manifests itself in Polynomial Regression.
- Through fitting data too loosely
- Through fitting data with low-degree polynomials
- Through fitting noise and showing oscillatory behavior
- Through underfitting the model
Overfitting in Polynomial Regression is characterized by fitting the noise in the data and showing oscillatory behavior. A high-degree polynomial can capture minute fluctuations, leading to a complex model that doesn't generalize well.
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