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Table 2 Rate and MSE obtained by running the algorithm proposed in [39] on the PhiX dataset

From: QualComp: a new lossy compressor for quality scores based on rate distortion theory

LogBinning R MSE   UniBinning R MSE   Truncating R MSE
60 0 836.54   2 0.08 629.25   33 0.30 189.63
32 0.78 352.20   4 0.10 493.59   40 0.35 165.27
30 0.76 207.50   6 0.11 452.24   60 0.42 142.76
25 0.63 102.14   10 0.15 339.58   70 0.50 122.08
20 0.41 118.67   20 0.22 243.96   80 0.59 103.19
15 0.9 39.86   30 0.26 215.86   90 0.59 103.19
10 1.09 17.67   60 0.42 142.76     
6 1.36 8.13   70 0.50 122.08     
4 1.90 2.92   80 0.59 103.19     
2 2.74 0.54   90 0.59 103.19     
  1. MSE obtained by the LogBinning, UniBinning and Truncating schemes proposed in [39] with different parameters.