Practice Entropy (5.3.2) - Supervised Learning - Classification Fundamentals (Weeks 6)
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Entropy

Practice - Entropy

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Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What does entropy measure in a dataset?

💡 Hint: Think about what it implies regarding the certainty of classification.

Question 2 Easy

What happens to entropy when a dataset is perfectly pure?

💡 Hint: Consider what a pure node would look like.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What does a higher entropy value signify in a dataset?

More certainty
More disorder
More information

💡 Hint: Consider what a mixed node would imply.

Question 2

True or False: A node with zero entropy contains both class A and class B.

True
False

💡 Hint: Reflect on the definition of entropy.

2 more questions available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

You are building a Decision Tree for classifying fruits based on features like color, weight, and size. Given the following class distribution of a specific node: 6 apples, 2 bananas, and 2 oranges, calculate the entropy for this node.

💡 Hint: Remember the formula for entropy and how to calculate probabilities.

Challenge 2 Hard

You have a dataset for loan approvals with three features: income, credit score, and home ownership status. Discuss how you would use entropy to evaluate potential splits in this dataset. What might high and low entropy indicate?

💡 Hint: Think of what each split signifies about the data distribution.

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