Practice Module Objectives (for Week 6) - 2 | Module 3: Supervised Learning - Classification Fundamentals (Weeks 6) | Machine Learning
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2 - Module Objectives (for Week 6)

Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What is the primary objective of Support Vector Machines?

πŸ’‘ Hint: Think about how SVMs handle classification.

Question 2

Easy

Define Gini impurity.

πŸ’‘ Hint: Consider it a measure of class certainty.

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 a hyperplane in the context of SVM?

  • A type of neural network
  • A decision boundary that separates classes
  • A measure of class uncertainty

πŸ’‘ Hint: Think about the role of a hyperplane in classification.

Question 2

True or False: Soft margin SVMs require perfect separation of classes.

  • True
  • False

πŸ’‘ Hint: Consider how soft margin handles data differently.

Solve 2 more questions and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Given a dataset with overlapping classes, determine whether a hard margin or soft margin SVM would yield better results. Justify your choice.

πŸ’‘ Hint: Consider the implications of misclassifications in relation to class overlap.

Question 2

Explain the trade-offs involved when pruning a Decision Tree. How does it impact model performance?

πŸ’‘ Hint: Focus on the balance between detail and generalization of the model.

Challenge and get performance evaluation