论文信息 - A survey on exact methods for minimum sum-of-squares clustering

A survey on exact methods for minimum sum-of-squares clustering

Minimum sum-of-squares clustering (MSSC) consists in partitioning a given set of n entities into k clusters in order to minimize the sum of squared distances from the entities to the centroid of their cluster. Among many criteria used for cluster analysis, the minimum sum-of-squares is one of the most popular since it expresses both homogeneity and separation. A mathematical programming formulation of MSSC is as follows:

P. Hansen | Daniel Aloise

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