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Table 2 Blind accuracies for various combinations of filtering and modeling methods

From: Cancer diagnosis marker extraction for soft tissue sarcomas based on gene expression profiling data by using projective adaptive resonance theory (PART) filtering method

Filtering methods

Wrapper methods

 

BFCS

FNN

SVM

MRA

kNN

WV

PART

81.1 ± 14.1 (8)

64.4 ± 15.6 (3)

73.3 ± 5.4 (2)

60.0 ± 16.6 (11)

67.8 ± 16.8 (10)

56.7 ± 13.6(14)

NSC

68.9 ± 6.7 (5)

60.0 ± 12.4 (3)

62.2 ± 13.3 (3)

65.6 ± 9.2 (9)

68.9 ± 13.0 (3)

66.7 ± 9.9 (21)

S2N

68.9 ± 6.7 (15)

56.7 ± 16.1 (3)

61.1 ± 15.9 (3)

61.1 ± 14.3 (4)

63.3 ± 17.2 (4)

58.9 ± 12.2 (18)

SAM

71.1 ± 7.4 (12)

64.4 ± 12.0 (3)

67.8 ± 13.6 (3)

63.3 ± 12.2 (10)

74.4 ± 8.7 (7)

63.3 ± 11.2 (9)

Student's t-test

71.1 ± 5.4 (15)

53.3 ± 12.0 (4)

60.0 ± 10.2 (13)

58.9 ± 13.2 (5)

68.9 ± 8.3 (4)

60.0 ± 19.4 (26)

U-test

66.7 ± 9.9 (9)

56.7 ± 16.1 (3)

64.4 ± 13.0 (7)

54.4 ± 10.2 (7)

67.8 ± 11.6 (14)

62.2 ± 12.4 (1)

Welch's t-test

65.6 ± 10.5 (15)

55.6 ± 14.9 (3)

58.9 ± 8.7 (13)

53.3 ± 12.2

67.8 ± 10.5

65.6 ± 13.6 (12)

No filtering

68.9 ± 9.7 (10)

58.9 ± 10.0 (3)

66.7 ± 15.7 (2)

61.1 ± 13.4 (3)

55.6 ± 15.7 (3)

57.8 ± 17.1 (26)

  1. Parenthesized values indicate the numbers of probes used in each model.