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ResearchFormerly WizWand

Node Classification on PPI (Micro-F1 and Macro-F1)

25.28Micro F1LINE
5.05210.303515.55520.8065Nov 12, 2019Nov 17, 2019Nov 23, 2019Nov 29, 2019Dec 5, 2019Dec 11, 2019Dec 17, 2019
Updated 8mo ago

Evaluation results

MethodLinks
LINETraining fraction (γ)=90%2019.1125.2820.59
Caps2NETraining fraction (γ)=90%2019.1125.0820.27
DeepWalkTraining fraction (γ)=90%2019.1125.0220.01
Node2VecTraining fraction (γ)=90%2019.1124.7519.66
EP-BTraining fraction (γ)=90%2019.1124.7420.36
DeepWalkTraining fraction (γ)=50%2019.1123.5218.73
Node2VecTraining fraction (γ)=50%2019.1123.3118.57
EP-BTraining fraction (γ)=50%2019.1123.318.96
Caps2NETraining fraction (γ)=50%2019.1123.1519.63
LINETraining fraction (γ)=50%2019.1123.0118.06
NodeSketchParameter Tuning Strategy=Tuned for each dataset2019.1221.0415.55
DAORParameter Tuning Strategy=Parameter-free2019.1219.0713.94
NetHashParameter Tuning Strategy=Tuned for each dataset2019.1218.8512.91
Caps2NETraining fraction (γ)=10%2019.1118.5215.2
EP-BTraining fraction (γ)=10%2019.1117.8213.8
DeepWalkParameter Tuning Strategy=Tuned once for all datasets2019.1217.2410.28
DeepWalkTraining fraction (γ)=10%2019.1117.1413.01
Node2VecTraining fraction (γ)=10%2019.111713.32
LINETraining fraction (γ)=10%2019.1116.5512.79
Node2VecParameter Tuning Strategy=Tuned for each dataset2019.1216.049.57
VERSEParameter Tuning Strategy=Tuned once for all datasets2019.1215.99.76
INH-MF2019.1215.59.55
HARP-DWalkMeta technique=HARP2019.1215.469.04
NetMFParameter Tuning Strategy=Tuned for each dataset2019.1215.038.74
LINE2019.1215.018.7
HOPEParameter Tuning Strategy=Tuned for each dataset2019.1214.698.13
HARP-LINEMeta technique=HARP2019.1212.676.25
DAOCParameter Tuning Strategy=Parameter-free2019.1212.567.25
GraRepParameter Tuning Strategy=Tuned for each dataset2019.125.831.52