Love thy neighbour: automatic animal behavioural classification of acceleration data using the K-nearest neighbour algorithm.

ABSTRACT: Researchers hoping to elucidate the behaviour of species that aren't readily observed are able to do so using biotelemetry methods. Accelerometers in particular are proving particularly effective and have been used on terrestrial, aquatic and volant species with success. In the past, behavioural modes were detected in accelerometer data through manual inspection, but with developments in technology, modern accelerometers now record at frequencies that make this impractical. In light of this, some researchers have suggested the use of various machine learning approaches as a means to classify accelerometer data automatically. We feel uptake of this approach by the scientific community is inhibited for two reasons; 1) Most machine learning algorithms require selection of summary statistics w

SUBMITTER: Bidder OR 

PROVIDER: S-EPMC3931648 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature