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Cluster analysis techniques require users to specify the number of clusters that they require. Six classes of approaches to choosing the number of clusters:

Most of the widely used cluster analysis algorithms can be highly misleading or can simply fail when most or all the observations have some missing values.

Cluster analysis refers to algorithms that group similar objects into groups called clusters. The endpoint of cluster analysis is a set of clusters, where each ...

What is k-means cluster analysis? An in depth look plus a step by step guide to perform k-means cluster analysis by data scientist Tim Bock of displayr.com

A dendrogram is a diagram that shows the hierarchical relationship between objects, often created as an output from hierarchical clustering. Read more.