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Table 3 AUPR and AUROC results for the compared methods. The tree-ensemble setting is the RF

From: Network inference with ensembles of bi-clustering trees

AUPR

Tn×Lm

Ln×Tm

Tn×Tm

Data

eBICT

GLSO

LOCMO

eBICT

GLSO

LOCMO

eBICT

GLSO

LOCMO

ern

0.399

0.386

0.404

0.049

0.047

0.055

0.065

0.052

0.052

dpie

0.613

0.607

0.6

0.32

0.302

0.323

0.175

0.155

0.167

dpii

0.518

0.5

0.496

0.341

0.324

0.342

0.065

0.068

0.07

dpig

0.233

0.226

0.219

0.35

0.318

0.329

0.085

0.077

0.069

dpin

0.39

0.333

0.367

0.502

0.481

0.495

0.105

0.1

0.095

srn

0.149

0.133

0.168

0.028

0.032

0.025

0.023

0.023

0.018

Avg

0.384

0.364

0.376

0.265

0.251

0.262

0.086

0.079

0.079

AUROC

Tn×Lm

Ln×Tm

Tn×Tm

ern

0.836

0.846

0.857

0.602

0.645

0.61

0.763

0.732

0.642

dpie

0.831

0.87

0.868

0.819

0.826

0.819

0.736

0.712

0.675

dpii

0.792

0.817

0.814

0.808

0.799

0.801

0.579

0.573

0.529

dpig

0.574

0.692

0.655

0.853

0.863

0.855

0.639

0.641

0.589

dpin

0.511

0.661

0.583

0.75

0.775

0.774

0.59

0.567

0.505

srn

0.812

0.779

0.806

0.518

0.569

0.532

0.558

0.558

0.496

Avg

0.726

0.778

0.764

0.725

0.746

0.732

0.644

0.631

0.573

  1. Best values appear in boldface