Seeing It All: Evaluating Supervised Machine Learning Methods for the Classification of Diverse Otariid Behaviours
PloS one, 2016-12, Vol.11 (12), p.e0166898-e0166898 [Peer Reviewed Journal]COPYRIGHT 2016 Public Library of Science ;COPYRIGHT 2016 Public Library of Science ;2016 Ladds et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2016 Ladds et al 2016 Ladds et al ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0166898 ;PMID: 28002450
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