dc.creator | Turesson, Hjalmar K. | |
dc.creator | Ribeiro, Sidarta Tollendal Gomes | |
dc.creator | Pereira, Danillo R. | |
dc.creator | Papa, João P. | |
dc.creator | Albuquerque, Victor Hugo C. de | |
dc.date.accessioned | 2016-09-29T14:47:27Z | |
dc.date.accessioned | 2022-10-06T13:52:21Z | |
dc.date.available | 2016-09-29T14:47:27Z | |
dc.date.available | 2022-10-06T13:52:21Z | |
dc.date.created | 2016-09-29T14:47:27Z | |
dc.date.issued | 2016-09 | |
dc.identifier | TURESSON, H.K.; RIBEIRO, S.; PEREIRA, D.R.; PAPA, J.P.; DE ALBUQUERQUE, V.H.C. Machine Learning Algorithms for Automatic Classification of Marmoset Vocalizations. PLoS ONE. v.11, n.9, p.e0163041, 2016. doi:10.1371/journal.pone.0163041 | |
dc.identifier | https://repositorio.ufrn.br/jspui/handle/123456789/21398 | |
dc.identifier.uri | http://repositorioslatinoamericanos.uchile.cl/handle/2250/3973372 | |
dc.description.abstract | Automatic classification of vocalization type could potentially become a useful tool for
acoustic the monitoring of captive colonies of highly vocal primates. However, for classification
to be useful in practice, a reliable algorithm that can be successfully trained on small
datasets is necessary. In this work, we consider seven different classification algorithms
with the goal of finding a robust classifier that can be successfully trained on small datasets.
We found good classification performance (accuracy > 0.83 and F1-score > 0.84) using the
Optimum Path Forest classifier. Dataset and algorithms are made publicly available. | |
dc.rights | Acesso Aberto | |
dc.subject | Machine Learning Algorithms | |
dc.subject | Marmoset Vocalizations | |
dc.title | Machine Learning Algorithmsfor Automatic Classification of Marmoset Vocalizations | |
dc.type | article | |