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Table 3 The mean precision, recall and F1 statistic (± SD) for each random forest model predicting behaviour or behaviour including slope of terrain for Alpine ibex and pygmy goats

From: Limitations of using surrogates for behaviour classification of accelerometer data: refining methods using random forest models in Caprids

Model Classification accuracy Mean precision Mean recall Mean F1 statistic
Random split behaviour 98.3% 0.95 ± 0.05 0.98 ± 0.018 0.96 ± 0.030
Random split behaviour including slope of terrain 98.2% 0.95 ± 0.042 0.98 ± 0.018 0.96 ± 0.024
Data split per individual behaviour 63.0% 0.48 ± 0.32 0.55 ± 0.27 0.46 ± 0.28
Data split per individual behaviour including slope of terrain 68.1% 0.36 ± 0.028 0.42 ± 0.082 0.034 ± 0.046
Pygmy goat predicting Alpine ibex behaviour 55.5% 0.55 ± 0.39 0.62 ± 0.10 0.48 ± 0.30
Pygmy goat predicting female Alpine ibex behaviour 60.2% 0.55 ± 0.39 0.50 ± 0.26 0.49 ± 0.32
Pygmy goat predicting Alpine ibex behaviour including slope of terrain 59.8% 0.29 ± 0.38 0.30 ± 0.29 0.27 ± 0.32
Pygmy goat predicting female Alpine ibex behaviour including slope of terrain 67.8% 0.28 ± 0.42 0.25 ± 0.34 0.26 ± 0.37
Randomly generated behaviours 15.4% 0.010 ± 0.27 0.058 ± 0.09 0.038 ± 0.08
Randomly generated behaviours with slope of terrain 26.4% 0.068 ± 0.24 0.040 ± 0.11 0.041 ± 0.12