After running PROC HPCLUS with NCLUST=4, two clusters appear very similar. Which metric best quantifies the separation between these two specific clusters?
Select an answer to reveal the explanation.
Short Explanation and Infographic
Here's the deal — b is correct because the distance between two specific cluster centroids directly quantifies how different those two clusters are in feature space. Small centroid distance indicates similar clusters that may be candidates for merging.
Full explanation below image
Full Explanation
B is correct because the distance between two specific cluster centroids directly quantifies how different those two clusters are in feature space. Small centroid distance indicates similar clusters that may be candidates for merging. A (WCSS) is a global compactness measure. C (pseudo-F) measures global separation vs. cohesion. D evaluates the overall benefit of the additional cluster globally.