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Table 10 ACT feature knock-out experiments for LR

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 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
  1. 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.