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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What advantage do decision trees have in terms of interpretability?
💡 Hint: Think about how you can trace back the model's decisions.
Question 2
Easy
Can decision trees handle both numerical and categorical data?
💡 Hint: Consider what types of features you find in datasets.
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
Why are decision trees considered interpretable?
- They use only linear models.
- They visualize decision-making paths clearly.
- They require extensive preprocessing.
- They cannot handle categorical data.
💡 Hint: Look for clarity in how decisions are represented.
Question 2
Are decision trees capable of handling mixed data types?
- True
- False
💡 Hint: Consider the structure of cultural data.
Solve and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Given a dataset with both numerical and categorical features, outline the steps you would take to prepare it for analysis using a decision tree.
💡 Hint: Consider the common preprocessing methods you learned.
Question 2
Critically analyze how the flexibility in handling mixed data types affects the usability of decision trees in a specific industry.
💡 Hint: Think about the types of data typically found in healthcare datasets.
Challenge and get performance evaluation