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Table 2 Comparison of SW-RASTER with various standard clustering algorithms

From: S-RASTER: contraction clustering for evolving data streams

  SW-RASTER Windowed k-means DStream DBStream
Macro clusters 4 4 3 2
Micro clusters 103 100 108 118
purity 0.93 0.94 0.96 0.97
SSQ 77.80 114.26 50.70 44.72
cRand 0.04 0.06 0.06 0.06
silhouette 0.18 0.18 0.21 0.27
Manhattan 00.11 0.12 0.13 0.13
  1. The best values in this comparison are listed in italics. The number of micro clusters is listed for the sake of completion but we abstain from making a judgment as the resulting macro clusters are more relevant. Our algorithm does well in this comparison, as evinced by the cRand, silhouette coefficient and Manhattan distance values