Table 2 Properties of network datasets

From: Integrating graph and reinforcement learning for vaccination strategies in complex networks

Network

Type

Nodes

Edges

Average degree

Max-degree

Clustering

Diameter

SYN-SF-100

Synthetic

100

291

5.8

29

0.14

5

SYN-SF-500

Synthetic

500

1491

6.0

85

0.07

5

SYN-SF-1000

Synthetic

1000

2991

6.0

111

0.04

6

SYN-ER-100

Synthetic

100

309

6.2

14

0.04

5

SYN-ER-500

Synthetic

500

1504

6.0

14

0.01

8

SYN-ER-1000

Synthetic

1000

2990

6.0

14

0.01

8

SYN-SW-100

Synthetic

100

200

4.0

6

0.40

10

SYN-SW-500

Synthetic

500

1000

4.0

7

0.37

16

SYN-SW-1000

Synthetic

1000

2000

4.0

7

0.37

17

SYN-SF-Community-100

Synthetic

100

273

5.5

17

0.26

7

SYN-SF-Community-500

Synthetic

500

1218

4.9

24

0.03

11

SYN-SF-Community-1000

Synthetic

1000

2924

5.8

38

0.02

10

SYN-ER-Community-100

Synthetic

100

238

4.8

12

0.06

6

SYN-ER-Community-500

Synthetic

500

1077

4.3

11

0.01

9

SYN-ER-Community-1000

Synthetic

1000

2149

4.3

11

0.00

10

N-netscience

Real-world

379

914

4.8

34

0.74

17

N-weaver

Real-world

64

177

5.5

21

0.60

6

N-mammalia

Real-world

171

363

4.2

12

0.74

23

N-tortoise

Real-world

283

418

3.0

11

0.43

8