|
Features
|
F1 score
|
Specificity
|
Sensitivity
|
Accuracy
|
Matthews Coef
|
AUC iP/R
|
|---|
|
B
|
72.33
|
91.61
|
68.28
|
84.84
|
62.14
|
78.97
|
|
N
|
50.05
|
94.10
|
38.20
|
77.88
|
40.75
|
60.12
|
|
C
|
69.38
|
89.39
|
66.91
|
82.87
|
57.58
|
76.30
|
|
M
|
69.61
|
90.83
|
65.37
|
83.44
|
58.53
|
75.06
|
|
BC
|
74.57
|
92.69
|
70.09
|
86.13
|
65.34
|
80.75
|
|
BCM
|
76.45
|
93.20
|
72.17
|
87.10
|
67.84
|
82.67
|
|
BNCM
|
76.78
|
93.49
|
72.23
|
87.33
|
68.37
|
82.89
|
- Results of feature knock-out experiments on the combined ACT training and development datasets for the logistic regression (LR) model (%). B – bag of words; N – named entities; C – contextual words surrounding proteins; M – MeSH descriptors.
