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Keywords: Supervised learning algorithms
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Journal Articles

Combined use of two supervised learning algorithms to model sea turtle behaviours from tri-axial acceleration data

L. Jeantet, F. Dell'Amico, M.-A. Forin-Wiart, M. Coutant, M. Bonola, D. Etienne, J. Gresser, S. Regis, N. Lecerf, F. Lefebvre, B. de Thoisy, Y. Le Maho, M. Brucker, N. Châtelain, R. Laesser, F. Crenner, Y. Handrich, R. Wilson, D. Chevallier
Journal: Journal of Experimental Biology
J Exp Biol (2018) 221 (10): jeb177378.
https://doi.org/10.1242/jeb.177378
Published: 23 May 2018
.... We identified behaviours from the acceleration data using two different supervised learning algorithms, Random Forest and Classification And Regression Tree (CART), treating the data from the adult animals as separate from the juvenile data. We achieved a global accuracy of 81.30% for the adult...
View article titled, Combined use of two <span class="search-highlight">supervised</span> <span class="search-highlight">learning</span> <span class="search-highlight">algorithms</span> to model sea turtle behaviours from tri-axial acceleration data
Open the PDF for Combined use of two <span class="search-highlight">supervised</span> <span class="search-highlight">learning</span> <span class="search-highlight">algorithms</span> to model sea turtle behaviours from tri-axial acceleration data in another window
Includes: Supplementary data