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Quiz: Clustering and PCA

5 questionsNo time limitPass: 60%+10 XP on first pass

Find natural groups in data without labels: k-means clustering, choosing k with the elbow method, scaling before clustering, describing each segment for a business team, and PCA to compress many features into two — with a learner-segmentation case study.

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  1. Question 1

    What does k-means need you to choose?

  2. Question 2

    In the elbow method, what do you look for?

  3. Question 3

    Why scale features before k-means?

  4. Question 4

    PCA keeps 2 of 6 components and explains 95% of the variance. What does that mean?

  5. Question 5

    After clustering, what makes segments useful to a business team?