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.
