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What is the best way to evaluate the quality of the model found by an...

What is the best way to evaluate the quality of the model found by an unsupervised algorithm like k-means clustering, given metrics for the cost of the clustering (how well it fits the data) and its stability (how similar the clusters are across multiple runs over the same data)?

A.

The lowest cost clustering subject to a stability constraint

B.

The lowest cost clustering

C.

The most stable clustering subject to a minimal cost constraint

D.

The most stable clustering

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