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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is the main goal of a Support Vector Machine?
💡 Hint: Think about what is being separated in the classification context.
Question 2
Easy
What does the term 'hyperplane' refer to?
💡 Hint: Consider dimensions when visualizing it.
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 the margin in SVMs represent?
- Distance between classes
- Distance between support vectors
- Distance between hyperplane and nearest data points
💡 Hint: It's about the closest points to the boundary.
Question 2
True or False: Decision Trees are highly interpretable models.
- True
- False
💡 Hint: Think about how easy it is to follow the path of decisions.
Solve 2 more questions and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
You are tasked with classifying a highly non-linear dataset. Which SVM kernel would you select, and why? Discuss the decision-making process.
💡 Hint: Think about the shape of the data!
Question 2
Consider a Decision Tree classifier that shows a high training accuracy but low test accuracy. What steps could you take to improve its performance?
💡 Hint: Consider how to simplify the tree!
Challenge and get performance evaluation