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Old 05-09-2013, 06:37 AM   #2
chadn737
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Location: US

Join Date: Jan 2009
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There are pros and cons to each approach. Hierarchical will give you a cluster of clusters. This could be an advantage or completely useless. Hierarchical clustering is also prone to outliers if I remember right. An outlier would form its own cluster entirely. On the other hand k-means requires you to define the number of clusters. This can be done by using the Gap statistic of Tibshirani.
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