Table 2 Comparison of Accuracy (in %).

From: Comparative analysis of machine learning models for detecting water quality anomalies in treatment plants

No. of Samples

HML14

ANN15

HDFM16

IMLM19

DLA20

ASSA22

MLF24

TDLM25

MOOM 27

Proposed

100

67.526

67.618

71.050

70.524

77.414

71.050

79.579

74.536

83.196

92.633

200

67.254

66.327

70.541

70.239

75.935

70.541

77.700

73.516

81.578

91.867

300

66.981

65.035

70.032

69.954

74.456

70.032

75.821

73.388

81.518

91.102

400

66.709

63.743

69.523

69.670

72.977

69.523

73.942

72.446

80.533

90.337

500

66.436

62.451

69.014

69.385

71.499

69.014

72.063

72.868

80.714

89.572

600

66.163

61.160

68.505

69.100

70.020

68.505

70.184

72.034

79.710

88.797

700

65.891

59.868

67.996

68.816

68.541

67.996

68.305

71.593

79.107

88.032

800

65.618

58.576

67.487

68.531

67.062

67.487

66.426

71.152

78.514

87.267

900

65.346

57.284

66.978

68.246

65.583

66.978

64.547

70.710

77.911

86.502

1000

65.073

55.993

66.469

67.962

64.104

66.469

62.668

70.269

77.308

85.737