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Agglomerative hierarchical clustering methods/procedures
Methods of cluster analysis that start with each individual in the separate cluster and then, in the series of steps, combine the individuals and later, it clusters into new larger clusters until a final stage is attained where all individuals are the members of a single group. At each stage or phase the individuals or clusters which are 'closest', in accordance to some particular definition of the distance are attached. The whole procedure can be summarized by the dendrogram. Solutions consequent to particular numbers of clusters are found by 'cutting' the dendrogram at the suitable level. See also average linkage, Ward's method, single linkage, complete linkage, K-means clusterAnalysis, Mojena's test and divisive methods or procedure.
importance of time series analysis?
#what is the importance of measures of central tendency to Human resource management
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