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. 2023 Oct 18;24:392. doi: 10.1186/s12859-023-05502-x

Table 8.

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

Methods Performance (RMSE)
Marginal Model Scenarios
I II III IV
Mean (95% Confidence Interval)
ALASSO 0.95
(0.95–0.96)
3.76
(3.67–3.84)
3.08
(3.01–3.14)
0.86
(0.81–0.90)
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)

Values in Bold means best results