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Table 3 Prediction performance of various methods on AUC (mean (SD)) across six scenarios and 100 duplicated runs

From: A non-negative spike-and-slab lasso generalized linear stacking prediction modeling method for high-dimensional omics data

 

Scenario 1

Scenario 2

Scenario 3

Scenario 4

Scenario 5

Scenario 6

Penalty and group penalty methods

Lasso

0.871 (0.018)

0.754 (0.023)

0.644 (0.029)

0.848 (0.018)

0.786 (0.024)

0.660 (0.028)

MCP

0.873 (0.018)

0.757 (0.023)

0.637 (0.032)

0.851 (0.019)

0.785 (0.027)

0.655 (0.028)

SCAD

0.873 (0.017)

0.756 (0.023)

0.640 (0.029)

0.851 (0.019)

0.786 (0.026)

0.660 (0.026)

network

0.849 (0.019)

0.755 (0.023)

0.634 (0.029)

0.867 (0.020)

0.780 (0.026)

0.658 (0.025)

gsslasso

0.875 (0.017)

0.758 (0.022)

0.644 (0.029)

0.855 (0.018)

0.788 (0.025)

0.659 (0.028)

grlasso

0.842 (0.018)

0.738 (0.023)

0.624 (0.028)

0.825 (0.020)

0.762 (0.024)

0.636 (0.028)

grMCP

0.815 (0.020)

0.724 (0.022)

0.620 (0.026)

0.801 (0.022)

0.748 (0.024)

0.631 (0.027)

grSCAD

0.851 (0.018)

0.738 (0.023)

0.624 (0.027)

0.832 (0.019)

0.765 (0.022)

0.635 (0.028)

cMCP

0.871 (0.019)

0.752 (0.025)

0.634 (0.034)

0.850 (0.022)

0.772 (0.027)

0.653 (0.030)

Model stacking methodsa

nsslasso (Lasso)

0.845 (0.017)

0.763 (0.020)

0.656 (0.026)

0.870 (0.017)

0.796 (0.021)

0.670 (0.026)

nsslasso (MCP)

0.850 (0.016)

–

–

–

–

0.670 (0.027)

nsslasso (SCAD)

0.850 (0.016)

–

–

–

–

0.671 (0.027)

nsslasso (network)

0.847 (0.016)

0.762 (0.020)

0.634 (0.029)

0.872 (0.018)

0.800 (0.022)

0.669 (0.025)

nsslasso (KNN)

0.785 (0.022)

0.706 (0.027)

0.597 (0.041)

0.809 (0.022)

0.738 (0.024)

0.617 (0.037)

nsslasso (NBa)

0.749 (0.024)

0.686 (0.029)

0.609 (0.029)

0.782 (0.022)

0.722 (0.024)

0.635 (0.025)

nsslasso (RF)

0.802 (0.019)

0.728 (0.023)

0.620 (0.032)

0.835 (0.021)

0.763 (0.023)

0.638 (0.026)

L-BFGS (Lasso)

0.845 (0.017)

0.765 (0.019)

0.659 (0.027)

0.869 (0.017)

0.796 (0.021)

0.673 (0.025)

nLasso (Lasso)

0.844 (0.017)

0.763 (0.020)

0.656 (0.026)

0.870 (0.017)

0.796 (0.021)

0.670 (0.025)

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BMC Bioinformatics

ISSN: 1471-2105

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