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Table 2 ANOVA analysis for prediction performance (AUC)

From: Prognostic gene signatures for patient stratification in breast cancer - accuracy, stability and interpretability of gene selection approaches using prior knowledge on protein-protein interactions

gene selection method

no. significant wins

network based

PAM

4

No

sigGenNB

3

No

sigGenSVM

2

No

SCAD

6

No

HHSVM

9

No

RFE

1

No

RRFE

6

Yes

graphK

2

Yes

graphkKp

1

Yes

networkSVM

1

Yes

PAC

0

Yes

aveExpPath

9

Yes

HubClassify

6

Yes

pathBoost

4

Yes

network based (average)

3.625

 

classical (average)

4.17

 
  1. PAM (prediction analysis of microarray data), sigGenNB (SAM + Naïve Bayes), sigGenSVM (SAM + SVM),SCAD-SVM, HHSVM (Huberized Hinge loss SVM), RFE (Recursive Feature Elimination), RRFE (Reweighted Recursive Feature Elimination), graphK (graph diffusion kernels for SVMs), graphKp (p-step random walk graph kernel for SVMs), networkSVM (Network-based SVM), PAC (Pathway Activity Classification), aveExpPath (average pathway expression), HubClassify (classification by significant hub genes), pathBoost.