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Test your understanding with targeted questions related to the topic.
Question 1
Easy
Define Simple Linear Regression.
π‘ Hint: Think about its components - how many variables are involved?
Question 2
Easy
What does MSE measure?
π‘ Hint: Consider what happens to errors when squared.
Practice 4 more questions and get performance evaluation
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
What does the term 'MSE' stand for in regression metrics?
π‘ Hint: Itβs a commonly used metric in regression.
Question 2
True or False: Increasing the degree of a polynomial regression model always improves its performance.
π‘ Hint: Consider how the model behaves with unseen data.
Solve 1 more question and get performance evaluation
Push your limits with challenges.
Question 1
Given a dataset that shows a clear quadratic relationship, what degree of polynomial regression would be most appropriate, and why?
π‘ Hint: Consider the shape of the data when plotting.
Question 2
Youβve trained a high-degree polynomial model but observe poor performance on test data. What steps can you take to improve your model?
π‘ Hint: What adjustments can you make to decrease overfitting?
Challenge and get performance evaluation