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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
Define Random Forest in your own words.
💡 Hint: Think about how multiple opinions can improve decision-making.
Question 2
Easy
What does bagging stand for?
💡 Hint: Focus on the words 'bootstrap' and 'aggregating'.
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 is the primary purpose of Random Forest?
- To average multiple predictions from single models
- To use a single decision tree
- To boost the performance of weak learners
- To reduce variance by aggregating multiple trees
💡 Hint: Think about how diversity in decisions improves outcomes.
Question 2
True or False: Random Forest only uses one decision tree for making predictions.
- True
- False
💡 Hint: Consider how a forest comprises many trees.
Solve 1 more question and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
You have a dataset with many features and some missing values. Describe how you would prepare this data for a Random Forest model.
💡 Hint: Focus on data cleaning and feature selection steps.
Question 2
Explain why Random Forest might outperform a single decision tree in practical applications.
💡 Hint: Think about how diversity can spread risk in decision-making.
Challenge and get performance evaluation