Question

_____ is frequently referred to as k-means clustering. agglomerative clustering divisive clustering non-hierarchical clustering optimization partitioning

Answer 1

The answer is non-hierarchical clustering.

Non-hierarchical clustering is frequently referred to as k-means clustering. This type of clustering does not require all possible distances to be computed in a large data set. This technique is primarily used for the analysis of clusters in data mining.

Answer 2

Non-hierarchical clustering is frequently referred as K-means clustering algorithm.

Explanation:

• Non-hierarchical cluster is always aimed at finding object groups that minimizes or maximizes certain evaluation criterion.  

• Most of the algorithms would assign the objects iteratively to various groups while searching certain optimal values of the provided criterion.  

• One such example of Non-hierarchical clustering is K-means clustering. It aimed at assigning objects to user defined numeric fields of k number of clusters.

• It is done in such a way that increases the cluster separation while decreases the inter cluster distance to its mean.

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