Skip to main content

Table 2 Stability of decision tree models. Up: the models built for up-regulated genes. Down: the models built for down-regulated genes. Noise: the number of noisy instances added into the training set. TP: the number of true positive genes predicted by models built on the original data. TP': the number of true positive genes predicted by models built on the noisy data. Loss: the number of positive instances correctly classified in the original data but mis-classified in the noisy data. Rescue: the number of positive instances correctly classified in the noisy data but mis-classified originally. FP: the number of newly added noise genes classified as positive. Each value is an average across 223 up-regulated or 223 down-regulated gene sets. The standard errors for loss, rescue and FP are all less than 0.2.

From: CAGER: classification analysis of gene expression regulation using multiple information sources

  

Predefined motifs

Auto motifs

 

Noise

TP

TP'

Loss

Rescue

FP

TP

TP'

Loss

Rescue

FP

Up

0

16.6

16.6

0.0

0.0

0.0

26.4

26.4

0.0

0.0

0.0

 

5

16.6

17.1

2.5

2.4

0.6

26.4

27.7

7.8

7.6

1.5

 

10

16.6

17.4

3.6

3.2

1.1

26.4

28.9

8.1

7.7

2.9

 

15

16.6

17.7

4.0

3.5

1.6

26.4

30.3

8.2

7.7

4.4

 

20

16.6

18.8

4.2

4.1

2.4

26.4

31.7

8.3

7.8

5.8

 

25

16.6

19.3

4.5

4.2

3.0

26.4

32.6

8.5

7.8

6.8

 

50

16.6

21.2

5.8

4.6

5.7

26.4

37.8

9.1

7.2

13.3

 

0

19.1

19.1

0.0

0.0

0.0

27.9

27.9

0.0

0.0

0.0

Down

5

19.1

19.6

2.0

2.0

0.5

27.9

29.1

7.3

7.0

1.5

 

10

19.1

20.5

2.7

2.9

1.1

27.9

29.6

8.0

6.8

2.9

 

15

19.1

20.7

3.2

3.2

1.6

27.9

30.6

8.1

6.6

4.1

 

20

19.1

20.9

3.8

3.5

2.1

27.9

30.9

8.8

6.5

5.3

 

25

19.1

21.2

4.1

3.6

2.6

27.9

32.8

8.5

6.6

6.9

 

50

19.1

22.6

5.3

3.6

5.2

27.9

37.8

9.7

6.2

13.4