Super machine learning: improving accuracy and reducing variance of behaviour classification from accelerometry

Super machine learning: improving accuracy and reducing variance of behaviour classification from accelerometry

Abstract Background Semi-automating the analyses of accelerometry data makes it possible to synthesize large data sets. However, when constructing activity budgets from accelerometry data, there are many methods to extract, analyse and report data and results. For instance, machine learning is a rob...

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Bibliographic Details
Main Authors: Monique A. Ladds, Adam P. Thompson, Julianna-Piroska Kadar, David J Slip, David P Hocking, Robert G Harcourt
Format: Article
Language:English
Published: BMC 2017-03-01
Series:Animal Biotelemetry
Subjects:
Behavioural classification
Marine mammal
Ethogram
Accelerometer
Machine learning
Super learner
Online Access:http://link.springer.com/article/10.1186/s40317-017-0123-1

Internet

http://link.springer.com/article/10.1186/s40317-017-0123-1

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