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. Author manuscript; available in PMC: 2010 Aug 31.
Published in final edited form as: J Am Stat Assoc. 2010 Jun 1;105(490):713–726. doi: 10.1198/jasa.2010.tm09415

Figure 2.

Figure 2

Sparse and standard 6-means clustering are applied to a simulated 6-class example. Left: The gap statistics obtained using the sparse 6-means tuning parameter selection method, as a function of the number of features with non-zero weights, averaged over 10 simulated data sets. Center: Boxplots of the CERs obtained using sparse and standard 6-means clustering on 100 simulated data sets. Right: The weights obtained using sparse 6-means clustering, averaged over 100 simulated data sets.

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