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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What does k-NN stand for?
💡 Hint: Think about the terminology used in classification tasks.
Question 2
Easy
Name one distance metric used in k-NN.
💡 Hint: Consider the different ways to measure distances.
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 represent?
- The number of neighbors
- The number of data points
- The model parameters
💡 Hint: It's related to the number of points used for voting.
Question 2
True or False: k-NN requires a training process.
- True
- False
💡 Hint: Think about how it operates when making predictions.
Solve 2 more questions and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Given a dataset with 10 features and 1,000 instances, describe how you would preprocess the data before applying k-NN.
💡 Hint: Focus on the impact of varying feature scales and relevance.
Question 2
Consider a k-NN model deployed in a recommendation system. How would you ensure the 'k' parameter is optimally set?
💡 Hint: Remember, balancing underfitting and overfitting is key!
Challenge and get performance evaluation