How to Find Undetected Similarities in Data

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This article shows how clustering — and the use of dendrograms — can help decision makers recognize similarities and differences that they would be unlikely to detect on their own.  Left open, however, is the interpretation of why specific instances fall into particular clustering patterns.  Those who are familiar with the analyzed data will likely perceive commonalities and differentiators that account for clustering at various levels – but they probably would not have been able to tease out those aspects without the aid of analytic software.  And that is the power of clustering.
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