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Table 1 Performance summary of CEEdge and PPIEdge feature types compared to gene-based feature type in RF models. “Win” indicates that the edge-based feature type outperformed gene-based feature type and “Lose” indicates that the gene-based feature type outperformed edge-based one. “SS” and “NSS” indicate that win/lose was statistically significant and not statistically significant respectively

From: Robust edge-based biomarker discovery improves prediction of breast cancer metastasis

Evaluation Metric Type

Feature

Win

Lose

Win

Lose

Equal

 

Type

SS

SS

NSS

NSS

/NaN

AUC

CEEDge

4

0

7

2

0

 

PPIEdge

7

4

1

1

0

F1-score (0.5 probability threshold)

CEEdge

12

0

0

0

1

 

PPIEdge

10

0

1

0

2

Kappa (0.5 probability threshold)

CEEdge

11

0

1

0

1

 

PPIEdge

8

0

2

1

2

F1-score (Optimal probability threshold)

CEEdge

4

1

6

2

0

 

PPIEdge

7

1

1

4

0

Kappa (Optimal probability threshold)

CEEdge

4

0

6

2

1

 

PPIEdge

6

0

3

3

1