R package for animal behavior classification from accelerometer data—rabc |
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Authors: | Hui Yu Marcel Klaassen |
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Institution: | 1. Centre for Integrative Ecology, School of Life and Environmental Sciences, Deakin University, Geelong Vic, Australia ; 2. Druid Technology Co., Ltd., Chengdu China |
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Abstract: | Increasingly, animal behavior studies are enhanced through the use of accelerometry. To allow translation of raw accelerometer data to animal behaviors requires the development of classifiers. Here, we present the “rabc” (r for animal behavior classification) package to assist researchers with the interactive development of such animal behavior classifiers in a supervised classification approach. The package uses datasets consisting of accelerometer data with their corresponding animal behaviors (e.g., for triaxial accelerometer data along the x, y and z axes arranged as “x, y, z, x, y, z,…, behavior”). Using an example dataset collected on white stork (Ciconia ciconia), we illustrate the workflow of this package, including accelerometer data visualization, feature calculation, feature selection, feature visualization, extreme gradient boost model training, validation, and, finally, a demonstration of the behavior classification results. |
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Keywords: | accelerometer animal behavior classification data visualization interactive process XGBoost |
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