Balanced clustering

Balanced clustering

Balanced clustering is a special case of clustering, where in the strictest.sense, the cluster sizes are constrained to ⌊ n k ⌋ or ⌈ n k ⌉ , where n is the number of points and k is the number of clusters. This type of balanced clustering is called balance-constrained clustering. Typical algorithm is Balanced k-Means, which minimizes mean square error (MSE). There is also another type of balanced clustering, it is called balance-driven clustering. In it the cost function is two-objective that minimizes both imbalance and MSE. Typical cost functions are Ratio cut and Ncut.