Table 3 Feature importance of PVs over 100 permutational resampling on AD prediction.

From: Machine learning-guided determination of Acinetobacter density in waterbodies receiving municipal and hospital wastewater effluents

Rank

KNN

RF

XGB

SVR

M5P

MARS

PE

MDt_loss

%MDt loss

PE

MDt_loss

%MDt loss

PE

MDt_loss

%MDt loss

PE

MDt_loss

%MDt loss

PE

MDt_loss

%MDt loss

PE

MDt_loss

%MDt loss

0

Baseline

0.6231

0

Baseline

0.9198

0

Baseline

1.0670

0

Baseline

0.5226

0

Baseline

0.9206

0

TSS

1.1912

233.28

1

SAL

0.2799

44.92

TEMP

0.4222

45.90

TEMP

0.4588

43.00

DO

0.2094

40.06

TEMP

0.4656

50.58

BOD

0.9343

182.96

2

BOD

0.2660

42.69

DO

0.3240

35.23

BOD

0.4119

38.60

BOD

0.1869

35.77

DO

0.3704

40.23

Baseline

0.5107

100.00

3

TEMP

0.2645

42.45

BOD

0.3169

34.46

DO

0.3853

36.11

TEMP

0.1665

31.87

BOD

0.3241

35.20

SAL

0.5062

99.14

4

DO

0.2532

40.64

TSS

0.2254

24.51

SAL

0.3124

29.27

TSS

0.1403

26.85

SAL

0.2180

23.68

TEMP

0.4839

94.76

5

pH

0.1818

29.18

SAL

0.2034

22.11

TSS

0.2911

27.28

pH

0.1249

23.91

pH

0.1673

18.17

DO

0.2181

42.72

6

TSS

0.1528

24.53

pH

0.1572

17.10

pH

0.2159

20.24

SAL

0.1240

23.73

TSS

0.1516

16.46

pH

0.0000

0.00

Rank

Cubist

BRT

NNT

DTR

ENR

ANET33

PE

MDt_loss

%MDt loss

PE

MDt_loss

%MDt loss

PE

MDt loss

%MD loss

PE

MDt_loss

%MDt loss

PE

MDt_loss

%MDt loss

PE

MDt_loss

%MDt loss

0

Baseline

1.0418

0

Baseline

0.6785

0

Baseline

0.3525

0

Baseline

0.4657

0

Baseline

0.2147

0

Baseline

0.1218

0

1

TEMP

0.5294

50.82

TEMP

0.3044

44.87

TEMP

0.2424

68.77

TEMP

0.2682

57.58

DO

0.0562

26.19

SAL

0.0633

51.94

2

SAL

0.3795

36.43

BOD

0.2206

32.51

TSS

0.1284

36.42

BOD

0.1636

35.13

BOD

0.0469

21.84

TEMP

0.0559

45.86

3

BOD

0.3262

31.31

DO

0.1931

28.47

BOD

0.0736

20.88

pH

0.1101

23.64

SAL

0.0160

7.45

TSS

0.0529

43.43

4

DO

0.3118

29.93

TSS

0.1259

18.56

pH

0.0532

15.09

DO

0.0866

18.60

TSS

0.0146

6.80

DO

0.0424

34.82

5

TSS

0.2779

26.68

SAL

0.1072

15.80

DO

0.0354

10.04

TSS

0.0409

8.78

TEMP

0.0135

6.29

BOD

0.0418

34.29

6

pH

0.2190

21.02

pH

0.0799

11.77

SAL

0.0010

0.29

SAL

0.0252

5.40

pH

0.0035

1.65

pH

0.0128

10.47

Rank

ANET42

ANET10

ELM

LR

LRSS

GBM

PE

MDt_loss

%MDt loss

PE

MDt_loss

%MDt loss

PE

MDt_loss

%MDt loss

PE

MDt_loss

%MDt loss

PE

MDt_loss

%MDt loss

PE

MDt_loss

%MDt loss

0

Baseline

0.1389

0

Baseline

0.1662

0

Baseline

0.1858

0

Baseline

0.2129

0

Baseline

0.2115

0

Baseline

0.3633

0

1

TEMP

0.1143

82.31

TEMP

0.1384

83.30

TEMP

0.1059

57.00

BOD

0.0584

27.42

DO

0.0899

42.51

BOD

0.0812

22.35

2

SAL

0.0946

68.13

SAL

0.1359

81.76

BOD

0.0430

23.17

DO

0.0584

27.41

BOD

0.0669

31.65

TEMP

0.0793

21.84

3

BOD

0.0903

65.00

DO

0.1021

61.45

TSS

0.0344

18.52

TSS

0.0233

10.93

TSS

0.0233

11.01

TSS

0.0510

14.05

4

pH

0.0567

40.82

BOD

0.0680

40.94

SAL

0.0227

12.23

SAL

0.0101

4.75

SAL

0.0115

5.45

DO

0.0491

13.51

5

TSS

0.0381

27.41

pH

0.0559

33.66

DO

0.0025

1.32

TEMP

0.0058

2.73

pH

0.0045

2.11

SAL

0.0160

4.41

6

DO

0.0361

26.02

TSS

0.0546

32.84

pH

− 0.0042

− 2.27

pH

0.0051

2.41

TEMP

0.0000

0.00

pH

0.0148

4.07

  1. MDt_loss mean_dropout_loss, \(\%MDt loss=\mathrm{MDt}\_\mathrm{loss due to a PV}/baseline.\)