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Clustering
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Choosing K
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827.
Why WCSS Decreases with K
easy
The elbow method for choosing K plots WCSS against K. Why does WCSS always decrease as K increases?
A
More clusters means the algorithm runs more iterations, finding a better global minimum each time
B
More clusters eliminates outliers by assigning them to dedicated single-point clusters
C
More clusters reduces variance within each cluster by averaging over fewer points per centroid
D
More clusters means each point is assigned to a closer centroid, always reducing total squared distances
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