Cluster Analysis

Part of the Use R! book series (USE R)

The aim of unsupervised classification, or cluster analysis, is to organize observations into similar groups. Cluster analysis is a commonly used, appealing, and conceptually intuitive, statistical method. Some of its uses include market segmentation, where customers are grouped into clusters with similar attributes for targeted marketing; gene expression analysis, where genes with similar expression patterns are grouped together; and the creation of taxonomies of animals, insects, or plants. A cluster analysis results in a simplification of a dataset for two reasons: first, because the dataset can be summarized by a description of each cluster, and second, because each cluster, which is now relatively homogeneous, can be analyzed separately. Thus, it can be used to effectively reduce the size of massive amounts of data.


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© Springer Science+Business Media, LLC 2007

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