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Table 9 ACT feature knock-out experiments for SVM

From: Detecting experimental techniques and selecting relevant documents for protein-protein interactions from biomedical literature

Features

F1 score

Specificity

Sensitivity

Accuracy

Matthews Coef

AUC iP/R

B

73.45

93.02

67.95

85.75

64.19

72.44

N

31.75

98.07

19.76

75.35

31.50

42.04

C

69.47

93.58

61.58

84.30

60.03

69.98

M

69.07

91.63

63.56

83.49

58.33

68.33

BC

74.93

94.10

68.55

86.69

66.50

73.92

BCM

76.71

94.33

70.86

87.52

68.70

76.00

BNCM

77.01

94.48

71.08

87.69

69.14

76.22

  1. Results of feature knock-out experiments on the combined ACT training and development datasets (%) with Support Vector Machine (SVM). B – bag of words; N – named entities; C – contextual words surrounding proteins; M – MeSH descriptors.
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BMC Bioinformatics

ISSN: 1471-2105

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