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Table 2 Classification matrices of the LDA models for discrimination between non-aged (control) and aged seeds using spectral signatures (at 20 wavelengths) extracted from multispectral images of cowpea seeds

From: Utilization of computer vision and multispectral imaging techniques for classification of cowpea (Vigna unguiculata) seeds

Data set Two-class classification   Five-class classification
   Non-aged Aged % Correct   Non-aged AA24 AA48 AA72 AA96 % Correct
Training (n = 401) Non-aged 72 9 88.89% Non-aged 75 3 3 0 1 91.46%
  Aged 1 319 99.69% AA24 1 77 3 0 0 95.06%
  Overall correct classification    97.51% AA48 0 0 57 3 12 79.17
      AA72 0 1 7 71 6 83.53%
      AA96 0 0 9 6 66 81.48%
       Overall correct classification      86.28%
Cross-validation (n = 401) Non-aged 69 12 85.19 Non-aged 71 6 3 0 2 86.59%
  Aged 1 319 99.69 AA24 1 75 4 1 0 92.59%
  Overall correct classification    96.76 AA48 0 2 53 3 14 73.61
      AA72 0 1 9 67 8 78.82%
      AA96 0 1 10 7 63 77.78%
       Overall correct classification      82.04
Validation (n = 100) Non-aged 16 3 84.21 Non-aged 17 1 0 0 0 94.44%
  Aged 0 81 100 AA24 0 17 0 2 0 89.47%
  Overall correct classification    97.0 AA48 0 1 20 2 5 71.43
      AA72 0 0 1 15 0 93.75%
      AA96 0 0 1 0 18 94.74%
       Overall correct classification      87.00