What is the mathematical criterion that K-Means attempts to minimize, and how does it relate to centroid initialization?
- Maximizing centroid distances to data points
- Maximizing inter-cluster distance
- Minimizing the number of clusters
- Minimizing the sum of squared distances to centroids
K-Means minimizes the sum of squared distances from each point to its assigned centroid. Centroid initialization affects how quickly this criterion is minimized and the quality of the final clusters.
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