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        <title>Hierarchical methods</title>
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Hierarchical cluster analysis methods involve building a hierarchy of clusters, starting from the smallest (consisting of single objects) and ending with the largest (consisting of the maximum number of objects). Clusters are created on the basis of object similarity matrix.</description>
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        <description>K-means method

K-means method is based on an algorithm initially proposed by Stuart Lloyd and published in 1982 . In this method, objects are divided into a predetermined number of  clusters. The initial clusters are adjusted during the agglomeration procedure by moving objects between them so that the variation of objects within the cluster is as small as possible and the cluster distances are as large as possible. The algorithm works on the basis of the matrix of Euclidean distances between o…</description>
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