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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What does the 'k' represent in the k-NN algorithm?
💡 Hint: Think about how many neighbors influence the prediction.
Question 2
Easy
Name one advantage of k-NN.
💡 Hint: Consider its ease of understanding.
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 does 'k' in k-NN refer to?
- A distance metric
- Number of neighbors considered
- The training set size
💡 Hint: Think about how many examples help predict the new data point.
Question 2
True or False: k-NN requires a training phase where models are built.
- True
- False
💡 Hint: Remember how k-NN works at prediction time.
Solve 2 more questions and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
You are tasked to classify a new fruit sample using k-NN. The training set includes apples, oranges, and bananas, each described by weight and color. Explain how you would implement k-NN in this scenario.
💡 Hint: Focus on how weights and colors interact in the feature space.
Question 2
You have a dataset with features that vary in scale from very small to very large. Describe how you would prepare this data for a k-NN model to ensure it performs adequately.
💡 Hint: Think about why differences in scale might mislead distance calculations.
Challenge and get performance evaluation