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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is the main purpose of PCA?
💡 Hint: Think about how we simplify data without losing significant information.
Question 2
Easy
What do we call the new variables resulting from PCA?
💡 Hint: Remember the role they play in data representation.
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 is the primary goal of PCA?
- To increase the dimensions of data
- To reduce the dimensions of data
- To randomize data
💡 Hint: Think about the overall purpose of data analysis.
Question 2
True or False: PCA can only be used for linear datasets.
- True
- False
💡 Hint: Consider the types of data PCA works best with.
Solve 1 more question and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Given a high-dimensional dataset of images, explain how PCA can assist in visualizing these images more effectively. What considerations must be kept in mind during this transformation?
💡 Hint: Think about what features are most important in an image.
Question 2
Suppose you have applied PCA and retained three principal components. How would you evaluate if these components are adequate for a particular analysis?
💡 Hint: Reflect on how variance retention impacts analysis outcomes.
Challenge and get performance evaluation