MOTIF_LP

The complex networks are sampled using read.py
The properties of sampled networks are determined using density.py
The simple version of the proposed motif-based link prediction metric (and its variants) is coded in metric.py (and metric2.py and metric3.py)
The signed version of the proposed motif-based link prediction metric (and its variants) is coded in metric_sign.py (and metric_sign2.py)
The visualizations are generated using viz.py (and plot.py and plot2.py)

Name		Name	Last commit message	Last commit date
Latest commit History 4 Commits
AUC-Sign.png		AUC-Sign.png
C0.p		C0.p
C1.p		C1.p
C2.p		C2.p
Change-all-k.p		Change-all-k.p
Dist.png		Dist.png
F.p		F.p
H.p		H.p
Main.py		Main.py
Metric Variant.png		Metric Variant.png
README.md		README.md
Rule-Accuracy.png		Rule-Accuracy.png
Rule-Density.png		Rule-Density.png
V.p		V.p
VaryK.png		VaryK.png
Yeast.gml		Yeast.gml
change_k.py		change_k.py
density.py		density.py
dist.py		dist.py
eC.p		eC.p
metric.py		metric.py
metric2.py		metric2.py
metric3.py		metric3.py
metric_sign.py		metric_sign.py
metric_sign2.py		metric_sign2.py
metric_walk.py		metric_walk.py
plot.py		plot.py
plot2.py		plot2.py
read.py		read.py
read2.py		read2.py
res_metric.txt		res_metric.txt
triad.py		triad.py
viz.py		viz.py

satunr/MOTIF_LP