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R package for animal behaviour classification from accelerometer data - rabc
  • Hui Yu,
  • Marcel Klaassen
Hui Yu
Deakin University Faculty of Science Engineering and Built Environment
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Marcel Klaassen
Deakin University Faculty of Science Engineering and Built Environment
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Abstract

Increasingly animal behaviour studies are enhanced through the use of accelerometry. To allow translation of raw accelerometer data to animal behaviours requires the development of classifiers. Here, we present the “rabc” package to assist researchers with the interactive development of such animal-behaviour classifiers based on datasets consisting out of accelerometer data with their corresponding animal behaviours. Using an accelerometer and a corresponding behavioural dataset collected on white stork (Ciconia ciconia), we illustrate the workflow of this package, including raw data visualization, feature calculation, feature selection, feature visualization, extreme gradient boost model training, validation, and, finally, a demonstration of the behaviour classification results.

Peer review status:POSTED

19 Nov 2020Submitted to Ecology and Evolution
21 Nov 2020Assigned to Editor
21 Nov 2020Submission Checks Completed