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Table 4 The results of feature selection on the discovery dataset performed by seven different RCPH models

From: Detecting prognostic biomarkers of breast cancer by regularized Cox proportional hazards models

Methods Training dataset (\(70 \%\)) Testing dataset (\(30 \%\))
# of features C-index ± Std. Dev P-value ± Std. Dev
Ridge-RCPH 1142 \(1.000 \pm 0.000\) \(0.013 \pm 0.001\)
Lasso-RCPH 47 \(0.726 \pm 0.022\) \(0.005 \pm 0.007\)
Enet-RCPH 66 \(0.798 \pm 0.044\) \(0.003 \pm 0.002\)
\(L_{1/2}\)-RCPH 4 \(0.629 \pm 0.000\) \(0.041 \pm 0.000\)
\(L_{0}\)-RCPH 17 \(0.794 \pm 0.000\) \(0.000 \pm 0.000\)
SCAD-RCPH 42 \(0.731 \pm 0.046\) \(0.032 \pm 0.018\)
MCP-RCPH 22 \(0.639 \pm 0.019\) \(0.062 \pm 0.044\)
  1. *Std. Dev Standard deviation