Cluster analysis aims at finding subsets (clusters) of a given set of entities, which are homogeneous and/or well separated. In the last decades, cluster analysis started playing an important role in a wide and heterogeneous range of applications involving different scientific research communities, including genetics, biology, biochemistry, mathematics, and computer science among others. This paper overviews the main types of clustering and criteria for homogeneity or separation, as well as the most popular solution techniques.
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