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What is the effect of minimizing the within-cluster sum of squares on the shapes of clusters produced in K-Means?

Using an objective function that minimizes the within-cluster sum of squares (WCSS) causes K-Means to produce spherically shaped clusters.

What loss function does K-Means seek to minimize?

K-Means minimizes the total within-cluster sum of squares (WCSS)

What is Within Cluster Sum of Squares (WCSS)?

The WCSS is a measure of the variability of observations within clusters.
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What are some common evaluation metrics in clustering?

Since there are no labels associated with the observations in unsupervised learning, there is no direct error metric that can be applied

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