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Table 4 Evaluation of learning model

From: Database application model and its service for drug discovery in Model-driven architecture

Dataset No.

Clustering

Correct rate (%)

Dataset No.

Clustering

Correct rate (%)

1

41 –100 %

100

5

34.7 –100 %

100

 

0.1 –100 %

100

 

27.4 –100 %

99.5

2

55 –100 %

23

 

12.1 –100 %

99.6

 

29 –100 %

95

 

0.1 –100 %

100

 

9 –100 %

40

6

53.2 –100 %

100

 

0.1 –100 %

100

 

51 –100 %

100

3

70.3 –100 %

100

 

50 –100 %

100

 

36 –100 %

90

 

34.7 –100 %

100

 

18 –100 %

20

 

27.4 –100 %

98

 

0.1 –100 %

86

 

18 –100 %

98

4

81.7 –100 %

100

 

12.1 –100 %

99

 

63.5 –100 %

100

 

0.1 –100 %

100

 

34.7 –100 %

100

7

81.7 –100 %

100

 

27.4 –100 %

100

 

49 –100 %

100

 

12.1 –100 %

100

 

18 –100 %

99

 

0.1 –100 %

100

 

0.1 –100 %

100

5

94 –100 %

100

   
  1. “Dataset No”. indicates 7 dataset patterns of pinpoint data shown in Table 2. “Clustering” indicates the approximated interval of prediction in side effect incidence of drug. “Correct rate” indicates to what extent each example of learning model can meet each correct interval in the prediction