Table 2

Holdout: accuracy criteria (to be maximized) for different numbers v of variables and different values of λ

v = 20

λ = 0

λ = 0.2

λ = 0.4

λ = 0.6

λ = 0.8

λ = 0.9

λ = 1

λ = 2


AUC

0.688

0.688

0.694

0.699

0.703

0.704

0.705

0.707

1-RMSE

0.460

0.466

0.481

0.493

0.504

0.510

0.515

0.542

SAR

0.559

0.561

0.569

0.575

0.580

0.583

0.585

0.595

F

0.255

0.254

0.260

0.262

0.265

0.265

0.266

0.274


W-L

1-0

3-0

5-0

6-0

5-0

5-0

5-0



v = 50

λ = 0

λ = 0.2

λ = 0.4

λ = 0.6

λ = 0.8

λ = 0.9

λ = 1

λ = 2


AUC

0.693

0.698

0.702

0.706

0.709

0.710

0.711

0.715

1-RMSE

0.451

0.458

0.465

0.471

0.477

0.479

0.482

0.503

SAR

0.552

0.556

0.562

0.567

0.571

0.572

0.574

0.583

F

0.263

0.265

0.268

0.270

0.272

0.271

0.273

0.277


W-L

2-0

3-0

3-0

2-0

2-0

3-0

4-0



v = 100

λ = 0

λ = 0.2

λ = 0.4

λ = 0.6

λ = 0.8

λ = 0.9

λ = 1

λ = 2


AUC

0.699

0.704

0.708

0.711

0.714

0.715

0.715

0.716

1-RMSE

0.454

0.457

0.459

0.463

0.467

0.470

0.472

0.487

SAR

0.545

0.549

0.553

0.557

0.561

0.563

0.564

0.573

F

0.272

0.271

0.272

0.274

0.274

0.274

0.275

0.284


W-L

1-0

1-0

1-0

2-0

3-0

4-1

4-1


AUC = Area Under the Curve; 1-RMSE = one minus Root Mean Squared Error; SAR = Squared error, Accuracy, and ROC; F = precision-recall; W-L = Win -Loss reporting the number of datasets for which the causal filter is significantly more (W) or less (L) accurate than the conventional ranking filter according both to the McNemar test (p-value < 0.05 adjusted for multiple testing by Holm's method) and the Wilcoxon paired test on squared errors (p-value < 0.05 adjusted for multiple testing by Holm's method).

Bontempi et al. BMC Bioinformatics 2011 12:458   doi:10.1186/1471-2105-12-458

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