Unsupervised Patterns

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1. Which explanation matches choose a clustering question?A. K-means alternates assigning points to centers and updating centers under a squared-distance objective.B. Hierarchical clustering builds a merge tree based on distance and linkage choices.C. Clustering seeks structure under a chosen representation and similarity measure.D. PCA finds orthogonal directions of maximum variance after suitable preprocessing.

2. Which explanation matches run and inspect k-means?A. Clustering seeks structure under a chosen representation and similarity measure.B. K-means alternates assigning points to centers and updating centers under a squared-distance objective.C. Hierarchical clustering builds a merge tree based on distance and linkage choices.D. PCA finds orthogonal directions of maximum variance after suitable preprocessing.

3. Which explanation matches hierarchical groups and their limits?A. Hierarchical clustering builds a merge tree based on distance and linkage choices.B. Clustering seeks structure under a chosen representation and similarity measure.C. K-means alternates assigning points to centers and updating centers under a squared-distance objective.D. PCA finds orthogonal directions of maximum variance after suitable preprocessing.

4. For run and inspect k-means, which result or action fits this practical case: The team asks k-means to form three route groups.A. Group deliveries by geography and schedule, then inspect whether groups are meaningful.B. Compare where two delivery groups join under single versus complete linkage.C. Project standardized training features onto two components, then apply the same transform to new trips.D. Run it from different initial centers and inspect cluster sizes.

5. For pca for compact representations, which result or action fits this practical case: Dozens of correlated route indicators make the dashboard crowded.A. Group deliveries by geography and schedule, then inspect whether groups are meaningful.B. Run it from different initial centers and inspect cluster sizes.C. Project standardized training features onto two components, then apply the same transform to new trips.D. Compare where two delivery groups join under single versus complete linkage.

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Unsupervised Patterns

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