Practice Polynomial Regression - 3.4 | Module 2: Supervised Learning - Regression & Regularization (Weeks 3) | Machine Learning
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3.4 - Polynomial Regression

Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What is polynomial regression?

πŸ’‘ Hint: Think about how it compares to linear regression.

Question 2

Easy

What are polynomial features?

πŸ’‘ Hint: Consider how these features are formed.

Practice 4 more questions and get performance evaluation

Interactive Quizzes

Engage in quick quizzes to reinforce what you've learned and check your comprehension.

Question 1

What does polynomial regression allow us to do?

  • A) Model only linear relationships
  • B) Model non-linear relationships using polynomial features
  • C) Eliminate the need for regression analysis

πŸ’‘ Hint: Think about how polynomial terms help capture curves.

Question 2

True or False: Higher-degree polynomials always improve model performance.

  • True
  • False

πŸ’‘ Hint: Consider the consequences of fitting noise in data.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Create a dataset that follows a non-linear trend and use polynomial regression to model it. Visualize the fit and discuss any patterns you observe.

πŸ’‘ Hint: Remember to check for any signs of overfitting or underfitting in the graph.

Question 2

Discuss how polynomial regression can be combined with regularization techniques to prevent overfitting. Provide specific examples of these techniques.

πŸ’‘ Hint: Think about how adding penalties affects the complexity of the model.

Challenge and get performance evaluation