Practice Gini Impurity (5.3.1) - Supervised Learning - Classification Fundamentals (Weeks 6)
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Gini Impurity

Practice - Gini Impurity

Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is Gini impurity?

💡 Hint: Think about classification accuracy.

Question 2 Easy

What Gini impurity value implies a pure node?

💡 Hint: Consider what purity means in classification.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What does a Gini impurity value of 0 signify?

All classes are mixed
All classes are pure
Some classes are overlapped

💡 Hint: Consider what purity means in classification terms.

Question 2

True or False: A higher Gini impurity indicates a more homogeneous dataset.

True
False

💡 Hint: Think of Gini impurity as a measure of mixture.

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Given a dataset of 50 samples, where 30 belong to Class A, 15 to Class B, and 5 to Class C, calculate the Gini impurity. What is the effect on Gini impurity after selecting a split that results in two child nodes, one consisting of all Class A and B samples and the other containing Class C?

💡 Hint: Always calculate Gini impurity for both initial and resultant nodes.

Challenge 2 Hard

In a decision tree where you realize Gini impurity continues to increase with splits constantly, suggest alternative nodes or strategies to help reduce impurity effectively.

💡 Hint: Think about tree complexity and its effect on generalization.

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Reference links

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