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Table 4 F1 score (precision, recall) of the baselines and the proposed method, named Combination

From: Learning adaptive representations for entity recognition in the biomedical domain

  Single representation Concatenation Combination
Entity SVM NN SVM NN MKL NN
chebi 69.67 70.46 75.29 76.96 78.99 76.87
  (88.84, 57.30) (92.44,56.93) (87.46, 66.08) (83.91, 67.62) (91.13, 69.70) (90.1766.98)
cell 79.91 80.12 79.91 79.91 80.16 80.12
  (88.41, 72.91) (88.92, 72.91) (88.41, 72.91) (88.41, 72.91) (89.01, 72.91) (88.92, 72.91)
go_cc 66.50 65.31 67.92 65.56 68.92 65.59
  (82.11, 55.87) (81.92, 54.30) (83.75, 57.12) (84.31, 54.63) (89.41, 56.06) (82.81, 54.30)
go_bpmf 30.84 30.49 30.29 30.29 36.20 30.64
  (68.59, 19.89) (69.72, 19.51) (70.96, 19.26) (70.32, 19.30) (78.73, 23.50) (71.34, 19.51)
organism 92.36 92.97 92.85 93.32 94.99 93.27
  (97.86, 87.45) (99.24, 87.45) (98.19, 88.07) (99.35, 87.97) (99.19, 91.13) (99.19, 8.02)
protein 72.68 81.94 82.26 81.09 81.68 84.38
  (77.63, 68.33) (81.41, 82.48) (84.40, 80.23) (85.53, 77.08) (85.44, 78.23) (88.73, 80.43)
sequence 72.26 72.61 71.77 72.47 75.08 72.51
  (89.58, 60.55) (88.79, 61.42) (88.67, 60.29) (89.10, 61.07) (93.11, 62.90) (90.43, 60.52)
  1. Best results are highlighted in bold characters