Table 8 RMSE performance of different wrapper methods on the real studies for test data

LASSO

0.96

(0.95–0.97)

3.75

(3.65–3.85)

3.10

(3.03–3.16)

0.84

(0.8–0.87)

SPLS

0.97

(0.95–0.99)

3.61

(3.54–3.69)

3.35

(3.03–3.66)

0.77

(0.76–0.79)

Enet

0.95

(0.94–0.96)

3.79

(3.7–3.87)

3.15

(3.08–3.23)

0.85

(0.81–0.90)

AEnet

0.96

(0.94–0.97)

3.76

(3.67–3.85)

3.11

(3.07–3.15)

0.84

(0.8–0.87)

AIWRAP-L

0.94

(0.93–0.94)

3.65

(3.59–3.71)

3.02

(2.98–3.06)

0.83

(0.8–0.86)

AIWRAP-LLr

0.96

(0.94–0.97)

3.59

(3.55–3.64)

2.97

(2.91–3.03)

0.75

(0.73–0.78)

AIWRAP-LR

0.95

(0.94–0.96)

3.80

(3.72–3.87)

3.19

(3.11–3.28)

1.20

(1.17–1.24)

Methods

Interaction Model Scenarios

I

II

III

IV

Mean (95% Confidence Interval)

ALASSO

0.94

(0.93–0.95)

3.69

(3.61–3.76)

3.12

(3.02–3.23)

0.52

(0.49–0.55)

GLASSO

1.44

(1.2–1.68)

4.46

(4.35–4.57)

8.24

(5.37–11.11)

0.31

(0.28–0.34)

LASSO

0.95

(0.94–0.96)

3.74

(3.67–3.81)

3.15

(3.02–3.27)

0.43

(0.39–0.47)

SPLS

1.03

(0.91–1.15)

3.81

(3.76–3.86)

4.34

(3.26–5.42)

0.24

(0.22–0.26)

Enet

0.94

(0.93–0.95)

3.78

(3.72–3.84)

3.24

(3.13–3.34)

0.44

(0.4–0.48)

AEnet

0.93

(0.92–0.94)

3.73

(3.65–3.81)

3.14

(3.06–3.21)

0.53

(0.5–0.56)

AIWRAP-L

0.94

(0.92–0.95)

3.58

(3.53–3.63)

3.07

(2.98–3.17)

0.29

(0.26–0.33)

AIWRAP-LLr

1.04

(0.99–1.1)

3.76

(3.58–3.93)

3.65

(3.26–4.04)

0.26

(0.21–0.31)

AIWRAP-LR

0.93

(0.92–0.94)

3.70

(3.64–3.76)

3.22

(3.18–3.26)

1.11

(0.99–1.24)