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Test your understanding with targeted questions related to the topic.
Question 1
Easy
What are 'residuals' in the context of GBM?
π‘ Hint: Think about how predictions can differ from actual outcomes.
Question 2
Easy
What is the purpose of the learning rate in GBM?
π‘ Hint: It prevents any one model from dominating the predictions.
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 GBM primarily focus on correcting?
π‘ Hint: Think about the learning process of each model.
Question 2
True or False: GBM combines predictions from models independently and simultaneously.
π‘ Hint: Consider whether the models communicate with each other in GBM.
Solve 1 more question and get performance evaluation
Push your limits with challenges.
Question 1
Given a regression problem with multiple features, how would you go about tuning the learning rate in a GBM model? Provide a detailed explanation.
π‘ Hint: Consider how slow adjustments can help avoid pitfalls of sudden learning.
Question 2
Discuss the implications of overfitting in GBM models and suggest methods to mitigate this issue.
π‘ Hint: Think about how many trees or models are used versus the depth of each.
Challenge and get performance evaluation