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Table 3 The clustering results of all methods on the different integrated datasets

From: Multi-cancer samples clustering via graph regularized low-rank representation method under sparse and symmetric constraints

Datasets

Measure

Method

K-means

T-SNE

LLE

NMF

PCA

LRR

LLRR

MLLRR

sgLRR

CO-CH

ACC

95.40

89.31

71.14

93.14

93.63

97.99

99.66

98.99

98.66

MCC

80.06

70.21

88.58

75.53

72.99

46.76

91.06

90.78

95.20

RI

91.43

49.85

63.66

87.18

88.07

96.04

99.32

98.00

97.34

NMI

66.46

51.01

75.71

54.12

54.47

41.92

80.51

77.04

87.51

PA-ES

ACC

98.25

91.84

77.26

99.16

99.16

96.38

99.16

99.16

99.16

MCC

84.73

83.74

62.04

98.34

98.34

77.98

96.71

96.71

98.34

RI

97.37

84.97

66.46

98.35

98.33

93.00

98.34

98.34

98.34

NMI

81.06

59.49

41.43

93.86

93.86

65.43

89.39

89.39

93.86

CH-HN-CO

ACC

89.22

83.03

80.99

76.99

85.77

95.86

97.99

84.77

98.28

MCC

67.91

65.69

60.77

82.25

69.17

61.23

68.31

80.96

87.25

RI

90.00

87.16

82.85

80.19

87.76

94.70

96.67

84.66

97.48

NMI

73.55

78.43

69.07

76.22

72.59

68.25

73.81

77.83

80.99

ES-CH-HN

ACC

85.56

52.35

61.65

84.52

80.03

82.17

93.19

94.32

96.11

MCC

66.26

32.62

42.01

67.44

66.08

43.04

61.18

66.49

91.32

RI

82.67

60.97

63.89

80.25

78.15

72.36

89.07

90.30

93.10

NMI

56.77

30.77

33.26

47.35

72.59

36.92

52.38

57.20

78.75

CO-CH-ES-HN

ACC

86.89

60.52

63.04

82.31

81.32

79.24

92.48

87.94

94.17

MCC

70.00

65.30

79.30

51.78

71.30

52.44

78.05

73.03

91.71

RI

89.43

74.59

71.98

85.07

86.57

81.58

91.42

88.95

93.34

NMI

71.04

48.43

52.00

57.67

69.12

54.76

74.42

69.82

80.27

ES-CO-PA-HN

ACC

86.89

85.83

67.76

82.31

81.32

79.24

92.48

87.94

94.17

MCC

79.51

78.52

77.40

84.23

89.82

59.21

88.38

83.63

85.49

RI

89.43

91.45

78.06

85.07

86.57

81.58

91.42

88.95

93.34

NMI

76.15

81.42

55.93

72.97

79.53

61.82

81.24

76.58

76.23

  1. Note: The best clustering results are highlighted in bold