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Table 5 Behavior-specific individual variation in model performance

From: Predicting moose behaviors from tri-axial accelerometer data using a supervised classification algorithm

Performance metric

Behavior

Lying_u

Ruminating

Foraging

Standing

Walking

Lying_o

Running

Recall

0.69 ± 0.17

0.74 ± 0.18

0.86 ± 0.04

0.53 ± 0.18

0.73 ± 0.14

0.78 ± 0.15

0.74 ± 0.21

Precision

0.82 ± 0.09

0.78 ± 0.12

0.89 ± 0.07

0.56 ± 0.18

0.57 ± 0.19

0.31 ± 0.31

0.28 ± 0.26

Prevalence (%)

34

24

21

14

4

3

0

  1. Behavior-specific variation in classification performance among 14 individuals of the random forest model classifying seven different behaviors from accelerometer data. Mean and standard deviation of precision and recall are given together with the prevalence of the behaviors in the observational data
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Animal Biotelemetry

ISSN: 2050-3385