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"M2B" package in R: Deriving multiple variables from movement data to predict behavioural states with random forests ArchiMer
Thiebault, Andrea; Dubroca, Laurent; Mullers, Ralf H. E.; Tremblay, Yann; Pistorius, Pierre A..
1. The behaviour of individuals affect their distributions and is therefore fundamental in determining ecological patterns. While, the direct observation of behaviour is often limited due to logistical constraints, collection of movement data has been greatly facilitated through the development of bio-logging. Movement data obtained through tracking instrumentation may potentially constitute a relevant proxy to infer behaviour. 2. To infer behaviour from movement data is a key focus within the "movement ecology" discipline. Statistical learning constitutes a number of methods that can be used to assess the link between given variables from a fully informed training dataset and then predict the values on a non-informed variable. We chose the random forest...
Tipo: Text Palavras-chave: Cape gannet; Fisheries; GPS; Local enhancement; Machine learning; Onboard observers; Social interactions; Video cameras.
Ano: 2018 URL:
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