Practice Week 6: Support Vector Machines (svm) & Decision Trees (3) - Supervised Learning - Classification Fundamentals (Weeks 6)
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Week 6: Support Vector Machines (SVM) & Decision Trees

Practice - Week 6: Support Vector Machines (SVM) & Decision Trees

Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is the main purpose of Support Vector Machines?

💡 Hint: Think about classification tasks and decision boundaries.

Question 2 Easy

Name a measure of impurity used in Decision Trees.

💡 Hint: These measures help evaluate how mixed the classes are.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is a hyperplane in the context of SVMs?

A margin separator
A type of kernel
A misclassified point

💡 Hint: Think about how classes are divided.

Question 2

True or False: Soft margin SVM allows for some misclassifications during classification.

True
False

💡 Hint: Consider the rigidity of hard margin SVM.

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Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Design a classification problem using both SVM and Decision Tree. Which one would you prefer for this scenario and why?

💡 Hint: Think about the context of the application and audience.

Challenge 2 Hard

Given a dataset with some noise and overlapping classes, describe how you would tune your SVM model’s parameters. Explain what to adjust and why.

💡 Hint: Contemplate the nature of the dataset's distribution.

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Reference links

Supplementary resources to enhance your learning experience.