Skip to main content

Table 1 Cross-validation classification accuracy (in percent) of various classification methods on the full four-class prostate cancer dataset using various numbers of peaks. Numbers are average observed accuracies over 100 runs with randomized 90/10 splits into training and test sets, respectively. The numbers in parentheses are the corresponding standard deviations.

From: Computational protein biomarker prediction: a case study for prostate cancer

 

# of peaks used

 

10

15

20

25

30

35

50

70

Quadr. Discr.

74.7 (7.4)

74.7 (9.6)

74.1 (8.4)

74.7 (7.1)

78.2 (6.8)

77.8 (7.3)

78.7 (6.6)

76.8 (7.1)

Nonpar (Kernel)

76.7 (7.1)

77.4 (8.4)

77.7 (6.9)

78.6 (6.6)

80.0 (6.3)

79.9 (7.3)

78.1 (6.5)

76.1 (7.6)

kNN

73.4 (7.4)

76.4 (6.9)

76.9 (6.0)

76.6 (6.1)

75.8 (6.7)

77.2 (6.9)

73.9 (7.5)

69.8 (6.7)

Fisher Linear

72.4 (7.3)

77.3 (6.9)

80.8 (6.5)

80.1 (5.8)

81.8 (6.0)

84.6 (5.2)

85.5 (6.1)

84.3 (5.1)

Linear SVM

75.4 (6.4)

79.3 (7.4)

81.7 (7.2)

81.3 (5.7)

83.7 (6.8)

83.1 (6.6)

83.5 (6.1)

84.0 (6.2)