Machine Learning & AI

Intermediate

K-Means Objective (WCSS)

Clustering minimizes the total squared distance of points to their cluster centre.

Formula

J = \sum_{k=1}^{K}\sum_{\mathbf{x}\in C_k}\lVert \mathbf{x}-\mu_k\rVert^2

Variables

C_kCluster k

\mu_kCentroid

KNumber of clusters

Example

Lower WCSS means tighter clusters

Did You Know?

K-means alternates assigning points and moving centroids — a special case of expectation-maximization.

clustering kmeans unsupervised

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