Question

When using the "elbow method" to select the optimal number of clusters K for K-means, at what point on the plot of Within-Cluster Sum of Squares (WCS

Q: Answer-When using the 'elbow method' to select the optimal number of clusters K for K-means, at what point...

WCSS also called inertia always decreases as K increases, reaching zero when K equals the number of data points so simply minimizing WCSS option A would always select the largest K tested, defeating the purpose of choosing a meaningful cluster count. The elbow method instead looks for the elbow point where the rate of WCSS decrease sharply flattens, indicating that adding more clusters beyond this point yields only marginal improvement in fit relative to the added model complexity.