Relocation clustering method

The best-known relocation method is the k-means method, for which there exist many variants and different algorithms for its implementation. The k-means algorithm minimizes the sum of the squared Euclidean distances between each item in a cluster and the cluster centroid. The basic method used most frequently in chemical applications proceeds as follows ... 

Note that the k-means relocation method is really a special case of EM that assumes (1) each cluster is modeled by a spherical Gaussian distribution, (2) each data item is assigned to a single cluster, and (3) the mixture weights... 

Nonhierarchical relocation methods, such as the k-means method, start with a user-defined number of seed clusters and iteratively reassign molecules between clusters to see if better clusters result, where the success of the solution is measured by some parameter such as the ratio of the mean intercluster similarity to the mean intracluster similarity, The methods can be quite... 

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