A team wants a centre-based grouping and a second view showing nested merges.
Which pairing describes the two clustering methods?
Retrieve earlier concepts before combining them.
This practice: Retrieve earlier concepts before combining them. Next: Retrieval 2 · Model-choice retrieval.
Supporting concepts: Explain a result responsibly →
Remember the idea
Use the inputs and evidence to recover the method. Hints and explained solutions remain collapsed; exact phrasing is not graded.
Hint 1 — Think
Recall which exploratory representation each method directly constructs.
Hint 2 — Tools
K-Means centroids and Ward merge hierarchy.
Hint 3 — Approach
Match the requested centre-based and nested views with their respective methods.
Explained solution
Both are exploratory. K-Means uses centroids; hierarchical clustering exposes a hierarchy that can be cut at several resolutions.
Both are exploratory. K-Means uses centroids; hierarchical clustering exposes a hierarchy that can be cut at several resolutions.
Helpful prior knowledge: Explain a result responsibly These links are guidance, not locks.
Sources and API context
Examples run with this Playground’s scikit-learn 1.4.2 / Pyodide 0.26.4 runtime.