#inertia

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Which statements about choosing the number of clusters are true? Select all that apply.

Running K-Means with as many clusters as there are (distinct) examples gives an inertia of 01
The elbow plot shows the trade-off between the within-cluster distances and the number of clusters2
Unlike the elbow method, the silhouette method does not depend on cluster centers3
The best number of clusters is the K with the smallest inertia4
Silhouette scores range from −1 to 1, and higher scores mean better cluster assignments5

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