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Table 9 Average number of true-positive and false-positive connections for three algorithms

From: Learning restricted Boolean network model by time-series data

K

Noise (%)

Algorithm

m = 10

m = 20

m = 30

m = 40

TP

FP

TP

FP

TP

FP

TP

FP

3

0

Three-rule

6.2

0

8.7

0.6

11.3

1.6

13.3

3.0

New

8.7

3.1

10.5

3.1

11.8

3.3

12.5

3.3

Best-fit

8.1

4.6

10.2

5.4

12.2

6.4

13.3

7.0

5

Three-rule

2.6

2.7

7.3

11.5

10.6

20.7

12.5

30.3

New

7.0

7.5

8.7

6.9

10.1

6.3

10.7

6.3

Best-fit

7.1

11.1

9.2

15.1

10.8

15.7

11.6

15.9

10

Three-rule

1.8

3.6

6.5

17.6

10.5

31.6

12.4

39.8

New

5.5

10.0

6.9

9.5

8.1

9.2

8.4

9.1

Best-fit

6.0

15.2

8.1

19.1

9.2

19.3

9.9

19.0

5

0

Three-rule

6.7

0.1

8.9

0.6

11.0

1.3

12.6

2.3

New

8.3

2.7

9.9

3.0

10.9

3.4

11.4

3.9

Best-fit

8.2

4.6

10.1

5.4

11.8

6.4

12.7

6.9

5

Three-rule

3.0

3.2

7.86

11.8

10.7

20.5

12.8

28.6

New

6.7

7.6

8.4

7.0

9.3

6.7

9.8

6.3

Best-fit

7.1

11.5

9.2

15.4

10.4

15.7

11.1

16.1

10

Three-rule

2.7

2.8

6.9

16.5

10.6

31.6

12.4

39.4

New

5.3

9.9

7.0

9.5

7.5

9.3

8.1

9.1

Best-fit

7.2

11.5

8.2

18.9

9.0

19.3

9.4

19.4