The MinMax k-Means clustering algorithm
We propose the MinMax k-Means algorithm to minimize the maximum intra-cluster variance objective. Weights are assigned to the clusters relative to their intra-cluster variance. Our method prevents the occurrence of clusters with large intra-cluster variances in the solution. Our method systematically uncovers high quality solutions, irrespective of the initialization. MinMax k-Means constitutes a sound approach for initializing k-Means.
k-means clustering k-means initialization balanced clusters