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Choosing the right loss function for multi-label Emotion Classification

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Choosing the right loss function for multi-label Emotion Classification

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Hurtado Oliver, LF.; González-Barba, JÁ.; Pla Santamaría, F. (2019). Choosing the right loss function for multi-label Emotion Classification. Journal of Intelligent & Fuzzy Systems. 36(5):4697-4708. https://doi.org/10.3233/JIFS-179019

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/139663

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Title: Choosing the right loss function for multi-label Emotion Classification
Author: Hurtado Oliver, Lluis Felip González-Barba, José Ángel Pla Santamaría, Ferran
UPV Unit: Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació
Issued date:
Abstract:
[EN] Natural Language Processing problems has recently been benefited for the advances in Deep Learning. Many of these problems can be addressed as a multi-label classification problem. Usually, the metrics used to evaluate ...[+]
Subjects: Deep Learning , Loss function , Multi-label classification , Natural Language Processing , Emotion Classification
Copyrigths: Reserva de todos los derechos
Source:
Journal of Intelligent & Fuzzy Systems. (issn: 1064-1246 )
DOI: 10.3233/JIFS-179019
Publisher:
IOS Press
Publisher version: https://doi.org/10.3233/JIFS-179019
Project ID:
UPV/PAID-01-17
AEI/TIN2017-85854-C4-2-R-AR
GENERALITAT VALENCIANA/PROMETEO/2018/176
Thanks:
This work has been partially supported by the Spanish MINECO and FEDER founds under project AMIC (TIN2017-85854-C4-2-R) and the GiSPRO project (PROMETEU/2018/176). Work of Jose-Angel Gonzalez is also financed by Universitat ...[+]
Type: Artículo

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