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Jul 16th, 2019
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  1. precision recall f1-score support
  2.  
  3. Nothing 0.96 0.90 0.93 7590
  4. B-SK 0.73 0.85 0.79 96
  5. I-SK 0.57 0.68 0.62 50
  6. B-LG 0.93 0.91 0.92 44
  7. I-LG 0.00 0.00 0.00 1
  8. B-NM 0.87 0.74 0.80 62
  9. B-AD 0.83 0.66 0.74 83
  10. B-PH 0.73 0.81 0.77 27
  11. B-MA 0.93 1.00 0.97 42
  12. B-CP 0.39 0.40 0.40 65
  13. I-CP 0.59 0.56 0.57 213
  14. B-WP 0.65 0.93 0.77 61
  15. I-WP 0.75 0.95 0.84 240
  16. B-PO 0.29 0.54 0.38 65
  17. I-PO 0.23 0.71 0.35 139
  18. B-IN 0.43 0.76 0.55 25
  19. I-IN 0.56 0.78 0.65 138
  20. B-FI 0.54 0.57 0.56 35
  21. I-FI 0.65 0.66 0.66 168
  22. B-EP 0.59 0.79 0.68 28
  23. I-EP 0.66 0.75 0.71 73
  24.  
  25. micro avg 0.87 0.87 0.87 9245
  26. macro avg 0.61 0.71 0.65 9245
  27. weighted avg 0.90 0.87 0.88 9245
  28. samples avg 0.87 0.87 0.87 9245
  29.  
  30. /usr/local/lib/python3.6/dist-packages/sklearn/metrics/classification.py:1437: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples.
  31. 'precision', 'predicted', average, warn_for)
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