Recall & Review
beginner
What is polynomial regression?
Polynomial regression is a type of regression analysis where the relationship between the input variable and the output variable is modeled as an nth degree polynomial. It helps capture curved patterns in data.
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beginner
Why use polynomial regression instead of linear regression?
Polynomial regression is used when data shows a curved or nonlinear relationship. Linear regression fits a straight line, which may not capture the true pattern if the data curves.
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beginner
How do you create polynomial features from a single input variable x?
You create new features by raising x to powers: x, x², x³, ..., up to the desired degree. These new features let the model fit curves instead of just a line.Click to reveal answer
intermediate
What is overfitting in polynomial regression?
Overfitting happens when the polynomial degree is too high, causing the model to fit noise in the training data instead of the true pattern. This leads to poor predictions on new data.
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beginner
How can you evaluate the performance of a polynomial regression model?
You can use metrics like Mean Squared Error (MSE) or R-squared on test data to see how well the model predicts. Lower MSE and higher R-squared mean better fit.
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What does polynomial regression model?
Which feature would you add for a 3rd degree polynomial regression?
What problem can happen if the polynomial degree is too high?
Which metric measures average squared difference between predicted and actual values?
Polynomial regression is a type of:
Explain how polynomial regression differs from linear regression and when you would use it.
Describe the risk of overfitting in polynomial regression and how it affects predictions.