In hierarchical clustering there is no requirement to predetermine the number of clusters.Select one:TrueFalse

Answer

The statement is True.

In hierarchical clustering, one of the key characteristics is that it does not require the user to specify the number of clusters in advance, unlike some other clustering algorithms such as K-means. Hierarchical clustering builds a tree of clusters, known as a dendrogram, by either merging clusters (agglomerative clustering) or splitting them (divisive clustering).

As the algorithm progresses, it allows for the visualization of the data at multiple levels of granularity. The user can then decide on the desired number of clusters by cutting the dendrogram at a specific height, rather than needing to define a specific number of clusters before running the algorithm. This flexibility makes hierarchical clustering a powerful technique for exploratory data analysis, as it provides insights into the data structure without forcing a pre-defined model.