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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.