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.