Practice Basic Idea (3.4.1) - Kernel & Non-Parametric Methods - Advance Machine Learning
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Basic Idea

Practice - Basic Idea

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Practice Questions

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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.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

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.

2 more questions available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

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.

Challenge 2 Hard

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.

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