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Table 4 Confusion matrices from three test models using four behaviours and 13 epochs

From: Super machine learning: improving accuracy and reducing variance of behaviour classification from accelerometry

  Foraging Grooming Resting Travelling Precision Sensitivity
Super learner
Foraging 1248 17 53 182 0.83 0.82
Grooming 18 1292 27 64 0.92 0.91
Resting 80 37 1321 61 0.88 0.89
Travelling 185 79 77 1158 0.77 0.79
Gradient boosting machine       
Foraging 1243 23 54 180 0.83 0.81
Grooming 20 1300 30 52 0.93 0.89
Resting 80 39 1305 76 0.87 0.90
Travelling 191 92 68 1149 0.77 0.79
Random forest       
Foraging 1220 25 57 198 0.81 0.80
Grooming 17 1291 42 52 0.92 0.90
Resting 86 35 1312 67 0.87 0.89
Travelling 195 88 59 1158 0.77 0.79