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Table 5 Performance measures of data mining algorithm at different levels of significance over Asthma dataset 4 classes

From: Comparative study of classification algorithms for immunosignaturing data

SIGNIFICANCE

p < 5 x 10-5

p < 5 x 10-4

p < 5 x 10-3

p < 5 x 10-2

 

Algorithm

Acc.

Sp

Sn

AUC

Acc.

Sp

Sn

AUC

Acc.

Sp

Sn

AUC

Acc

Sp

Sn

AUC

Avg.

Naïve Bayes

61.7

87.2

61.7

0.82

68.1

89.3

68.1

0.86

72.3

90.8

72.3

0.87

70.2

90.0

70.2

0.86

77.7

SLR

57.5

85.8

57.4

0.80

57.4

85.6

57.4

0.81

72.3

90.7

72.3

0.85

55.3

86.1

55.3

0.76

72.2

SVM

55.3

86.2

55.3

0.77

55.3

86.2

55.3

0.77

61.7

87.2

61.7

0.82

66.0

87.6

66.0

0.81

71.3

MLP

55.3

86.1

55.3

0.82

53.2

84.6

53.2

0.80

63.8

87.8

63.8

0.88

dnf

dnf

dnf

dnf

71.1*

Logistic R.

48.9

87.0

48.9

0.78

53.2

84.4

53.2

0.79

59.6

86.4

59.6

0.84

68.0

89.2

68.1

0.86

70.8

R. Forest

48.9

86.9

48.9

0.77

48.9

86.9

48.9

0.77

46.8

81.1

46.8

0.75

40.4

80.0

40.4

0.71

62.8

VFI

48.9

82.8

48.9

0.66

48.9

82.9

48.9

0.67

51.0

83.6

51.1

0.69

46.8

81.9

46.8

0.77

62.6

Hyper Pipes

51.1

83.4

51.1

0.72

53.2

84.0

53.2

0.70

46.8

71.8

46.8

0.74

42.6

80.3

42.0

0.75

62.3

M5P

48.9

82.8

48.9

0.79

55.3

86.1

55.3

0.81

42.5

81.0

42.6

0.68

27.6

75.8

27.7

0.57

60.0

KNN

42.5

87.1

42.6

0.69

46.8

86.6

46.8

0.67

44.6

88.0

44.7

0.69

36.2

79.7

36.2

0.67

59.6

K means

40.4

81.9

40.4

0.60

46.8

82.2

46.8

0.65

42.6

80.7

42.6

0.62

34.0

78.0

34.0

0.56

55.8

Bayes Net

38.3

79.3

38.3

0.56

36.2

77.8

36.2

0.56

44.7

81.4

44.7

0.63

36.2

77.6

36.2

0.60

53.9

K star

48.9

83.0

48.9

0.70

38.3

79.4

38.3

0.63

36.2

79.4

36.2

0.62

23.4

76.4

23.4

0.49

53.5

Random Tree

29.8

76.6

29.8

0.53

40.4

80.2

40.4

0.60

38.3

79.5

38.3

0.59

40.4

80.2

40.4

0.60

52.9

LDA

53.2

84.4

53.2

0.80

27.7

80.0

32.5

0.57

8.5

86.5

16.7

0.56

14.9

83.6

23.3

0.53

50.7

J48

27.7

75.4

27.7

0.52

27.7

75.9

27.7

0.49

42.6

80.8

42.6

0.58

31.9

77.1

31.9

0.52

48.7

ASC

27.7

76.0

27.7

0.52

19.2

71.8

19.1

0.46

29.8

76.7

29.8

0.52

21.2

74.8

21.3

0.45

43.1

  1. Acc: Accuracy, Sp: Specificity, Sn: Sensitivity, AUC: Area under ROC curve, Avg: Average score in % for each algorithms, dnf: Did not Finish”, * denotes Avg. from 3 significance levels. Measures >90% are marked in bold.