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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

Corresponding Author:[email protected]

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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.
19 Nov 2020Submitted to Ecology and Evolution
21 Nov 2020Submission Checks Completed
21 Nov 2020Assigned to Editor
07 Dec 2020Reviewer(s) Assigned
29 Mar 2021Review(s) Completed, Editorial Evaluation Pending
31 Mar 2021Editorial Decision: Revise Minor
27 May 20211st Revision Received
27 May 2021Submission Checks Completed
27 May 2021Assigned to Editor
27 May 2021Review(s) Completed, Editorial Evaluation Pending
28 May 2021Reviewer(s) Assigned
28 Jun 2021Editorial Decision: Revise Minor
02 Jul 20212nd Revision Received
02 Jul 2021Assigned to Editor
02 Jul 2021Submission Checks Completed
02 Jul 2021Review(s) Completed, Editorial Evaluation Pending
05 Jul 2021Editorial Decision: Accept