m2b - Movement to Behaviour Inference using Random Forest
Prediction of behaviour from movement characteristics
using observation and random forest for the analyses of
movement data in ecology. From movement information (speed,
bearing...) the model predicts the observed behaviour
(movement, foraging...) using random forest. The model can then
extrapolate behavioural information to movement data without
direct observation of behaviours. The specificity of this
method relies on the derivation of multiple predictor variables
from the movement data over a range of temporal windows. This
procedure allows to capture as much information as possible on
the changes and variations of movement and ensures the use of
the random forest algorithm to its best capacity. The method is
very generic, applicable to any set of data providing movement
data together with observation of behaviour.