Practice Comprehensive Comparative Analysis and Discussion - 6.2.4 | Module 3: Supervised Learning - Classification Fundamentals (Weeks 6) | Machine Learning
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6.2.4 - Comprehensive Comparative Analysis and Discussion

Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What is a hyperplane in the context of SVM?

💡 Hint: Think about visualizing a line or plane that divides classes.

Question 2

Easy

What does Gini impurity measure in a Decision Tree?

💡 Hint: Consider the likelihood of choosing a point that belongs to the wrong class.

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 main goal of an SVM?

  • To minimize the distance between classes
  • To maximize the margin between classes
  • To create a complex model

💡 Hint: Consider what the S in SVM stands for and the role of margins.

Question 2

True or False: Decision Trees can easily exhibit overfitting if no constraints are applied.

  • True
  • False

💡 Hint: Think about what overfitting means and how it relates to tree depth.

Solve 2 more questions and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

You are tasked with designing a classification model for a financial dataset that includes potential noise and outliers. Discuss which algorithms you would choose (SVM or Decision Tree) and defend your choice with at least three reasons. Consider how you might tune the model to manage overfitting.

💡 Hint: Look into problem characteristics and algorithm strengths.

Question 2

Critically analyze a dataset with highly overlapping classes and propose how you would visualize the decision boundaries if using both a Decision Tree and an SVM. Discuss how these boundaries might differ.

💡 Hint: Consider the geometrical aspects of decision boundaries.

Challenge and get performance evaluation