Question

Between Ward’s method and the centroid method for hierarchical clustering, which one can be considered the hierarchical counterpart of the (partitional) K-means?

Answer 1

Ans:

The answer is centroid method:

Brief explanation:

  For clustering large document datasets, partitional clustering algorithms are best and well suited. Though the quality of clustering is low, it is better than the agglomerative counterparts. So the centroid method is the one considered to be hierarchial counterpart of k-means(partitional).

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