Table 3 Comparison of prediction accuracy under the metric of Pearson correlation coefficient when only the weight information is missing for some links.

From: Weight prediction in complex networks based on neighbor set

Network\Index

Linear-correlation

Ours

CN

WCN

rWCN

AA

WAA

rWAA

RA

WRA

rWRA

Celegans

0.203

0.23

0.242

0.238

0.264

0.273

0.271

0.289

0.291

0.379

Everglades

0.137

0.177

0.415

0.141

0.291

0.455

0.157

0.271

0.406

0.799

USAir1

0.0403

0.554

0.305

0.0421

0.24

0.292

0.0712

0.224

0.218

0.513

USAir2

0.259

0.262

0.265

0.255

0.259

0.262

0.2

0.202

0.21

0.378

Advogato

0.234

0.262

0.289

0.247

0.275

0.303

0.255

0.274

0.314

0.4

Geom

0.181

0.332

0.45

0.207

0.34

0.496

0.19

0.246

0.517

0.545

  1. The validation set always contains 10% of the links from the example network. Each accuracy value is an average over 100 independent random divisions of links into a training set and a validation set. In each network, the best performance is emphasized in bold.
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