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Table 8 Comparison between multi-task learning and single task learning in a "mRNA" task level.

From: Multi-task learning for cross-platform siRNA efficacy prediction: an in-silico study

Test

RMSE

 

T1

T2

T3

T4

T5

T6

T7

T8

T9

T10

Test 6

22.9156

29.7953

24.4563

20.2755

13.6265

25.5433

28.6792

28.6911

13.8089

47.9704

Test 7

22.0309

28.8772

34.4272

22.4800

29.5645

22.3986

23.4719

42.3385

16.1072

34.2505

Test 8

22.2569

29.4852

22.9905

19.1120

11.7851

23.5123

29.9718

28.4760

11.7036

37.8482

 

T11

T12

T13

T14

T15

T16

T17

T18

T19

T20

Test 6

43.6353

13.9306

14.4649

5.6649

35.8113

33.6464

29.6981

29.4559

30.2422

21.0494

Test 7

35.4975

16.8432

13.0795

25.0440

26.3289

36.5158

29.9756

27.0347

26.0495

21.7607

Test 8

41.2163

18.2205

13.6913

5.7872

27.3318

27.5945

23.6955

26.5286

24.3853

16.2990

  1. "T" denotes "Task". Test 6: Selected 50% of the data from each experiment to train a regression model, and tested the model on the remain 50% of the data of each experiment, respectively. Test 7: Scaled all the experimental labels into [0,1] and pooling together 50% of the data from each experiment to train a general model, and tested the model on the remain 50% of the data of each experiment, respectively. Test 8: Multi-task learning for siRNA efficacy prediction, trained with 50% of the data from each experiment, respectively. p-value calculated by pair t-test on Test 6 and Test 7 is 0.5900. p-value calculated by pair t-test on Test 6 and Test 8 is 0.0033.