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R in Action, Second Edition: Data analysis and graphics with R by Robert Kabacoff

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Chapter 16. Cluster analysis

This chapter covers

  • Identifying cohesive subgroups (clusters) of observations
  • Determining the number of clusters present
  • Obtaining a nested hierarchy of clusters
  • Obtaining discrete clusters

Cluster analysis is a data-reduction technique designed to uncover subgroups of observations within a dataset. It allows you to reduce a large number of observations to a much smaller number of clusters or types. A cluster is defined as a group of observations that are more similar to each other than they are to the observations in other groups. This isn’t a precise definition, and that fact has led to an enormous variety of clustering methods.

Cluster analysis is widely used in the biological and behavioral sciences, ...

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