What is polynomial regression and how does it work?

What is polynomial regression and how does it work?

Polynomial regression is a form of regression analysis where the relationship between the independent variable x and the dependent variable y is modeled as an nth degree polynomial. It allows for modeling non-linear relationships.

Can you give me an example of when to use polynomial regression?

Sure! Polynomial regression is useful when the data shows a curvilinear relationship. For example, predicting the growth of plants over time might follow a quadratic curve.

How do I implement polynomial regression in Python?

You can use libraries like NumPy and scikit-learn. First, you fit a polynomial feature transformer to your data, then use a linear regression model on the transformed features.

What are the limitations of polynomial regression?

Some limitations include overfitting, especially with high-degree polynomials, and the difficulty in interpreting the model coefficients.