Analysis of Accelerometer Data Using Random Forest Models to Classify the Behavior of a Wild Nocturnal Primate: Javan Slow Loris (<i>Nycticebus javanicus</i>)

Analysis of Accelerometer Data Using Random Forest Models to Classify the Behavior of a Wild Nocturnal Primate: Javan Slow Loris (<i>Nycticebus javanicus</i>)

Accelerometers are powerful tools for behavioral ecologists studying wild animals, particularly species that are difficult to observe due to their cryptic nature or dense or difficult to access habitats. Using a supervised approach, e.g., by observing in detail with a detailed ethogram the behavior...

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Bibliographic Details
Main Authors: Amanda Hathaway, Marco Campera, Katherine Hedger, Marianna Chimienti, Esther Adinda, Nabil Ahmad, Muhammed Ali Imron, K. A. I. Nekaris
Format: Article
Language:English
Published: MDPI AG 2023-09-01
Series:Ecologies
Subjects:
animal behavior
supervised machine learning
random forest model
Online Access:https://www.mdpi.com/2673-4133/4/4/42

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