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Table 4 Performance of each method on downsampled data. The boldfaced numbers indicate the ones which outperformed the others

From: Feature selection using distributions of orthogonal PLS regression vectors in spectral data

Method MSE Q2 P N
OPLSRa αf=0.01 10,972 0.83 0.883 8.90
  αf=0.05 9,105 0.87 0.777 24.4
  αf=0.10 5,709 0.91 0.658 22.8
OPLSRb αf=0.01 10,133 0.85 0.884 10.4
  αf=0.05 8,811 0.89 0.881 31.0
  αf=0.10 7,782 0.93 0.848 48.2
FDR q=0.01 23,116 0.65 0.701 6.0
  q=0.05 10,330 0.85 0.685 39.5
  q=0.10 13,194 0.85 0.554 40.0
Lasso λ=0.01 6,235 0.90 0.502 6.3
  λ=0.10 9,886 0.88 0.494 3.2
  λ=0.50 13,124 0.80 0.498 2.1
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