ORFEO: Ordinal classifier and Regressor Fusion for Estimating an Ordinal categorical target

Authors
Antonio Manuel Gómez-Orellana
David Guijo-Rubio
Pedro Antonio Gutiérrez
César Hervás-Martínez
Víctor Manuel Vargas-Yun
Published in Journal

Engineering Applications of Artificial Intelligence

ENGINEERING, MULTIDISCIPLINARY

Impact Factor JCR 2024
8
JCR Ranking
Q1 D1
5 / 179
Position
ISSN 1873-6769
Vol. 133
No. E
Pages 108462

Abstract

In this paper we present a novel methodology, referenced as ORFEO (Ordinal classifier and Regressor Fusion for Estimating an Ordinal categorical target), to enhance the performance in ordinal classification problems for which the latent variable is observable. ORFEO is an artificial neural network model incorporating two outputs, one for ordinal classification, using the cumulative link model, and one for regression, using a linear model. Both outputs are simultaneously optimised considering a loss function that linearly combines both classification and regression losses. The main motivation behind developing the proposed approach is to enhance the performance of a standard ordinal classifier. This improvement is facilitated by considering the regression output, which allows the model to differentiate between patterns within the same category. The ORFEO model is applied to two problems in the field of marine and ocean engineering: short-term prediction of both significant wave height and flux of energy. Both problems are addressed considering four different coastal zones of the United States of America, using 13 datasets formed by buoys measurements and reanalysis data. A comprehensive comparison against 20 methodologies, including regression and nominal/ordinal classification approaches is performed, by using diverse nominal and ordinal performance metrics. Ranks achieved indicate that ORFEO outperforms all the compared methodologies in terms of all the performance measures, demonstrating the efficacy and robustness of the proposal. Finally, a statistical analysis is conducted, concluding that there are statistically significant differences across ordinal and nominal performance metrics in favour of the proposed ORFEO model.

Keywords

BibTex Citation
@article{Gomez2024ORFEO,
	author = {G{\' o}mez-Orellana, Antonio Manuel and Guijo-Rubio, David and Guti{\' e}rrez, Pedro Antonio and Herv{\' a}s-Mart{\' i}nez, C{\' e}sar and Vargas-Yun, V{\' i}ctor Manuel},
	journal = {Engineering Applications of Artificial Intelligence},
	doi = {10.1016/j.engappai.2024.108462},
	year = {2024},
	pages = {108462},
	title = {ORFEO: Ordinal classifier and {Regressor} {Fusion} for {Estimating} an {Ordinal} categorical target},
	url = {https://www.sciencedirect.com/science/article/pii/S0952197624006201?via%3Dihub},
	howpublished = {https://www.sciencedirect.com/science/article/pii/S0952197624006201?via\%3Dihub},
	volume = {133},
}
    
BibTex Unicode Citation
@article{Gomez2024ORFEO,
	author = {Gómez-Orellana, Antonio Manuel and Guijo-Rubio, David and Gutiérrez, Pedro Antonio and Hervás-Martínez, César and Vargas-Yun, Víctor Manuel},
	journal = {Engineering Applications of Artificial Intelligence},
	doi = {10.1016/j.engappai.2024.108462},
	year = {2024},
	pages = {108462},
	title = {ORFEO: Ordinal classifier and {Regressor} {Fusion} for {Estimating} an {Ordinal} categorical target},
	url = {https://www.sciencedirect.com/science/article/pii/S0952197624006201?via%3Dihub},
	howpublished = {https://www.sciencedirect.com/science/article/pii/S0952197624006201?via\%3Dihub},
	volume = {133},
}
    
APA Citation
Gómez-Orellana, A. M., Guijo-Rubio, D., Gutiérrez, P. A., Hervás-Martínez, C., & Vargas-Yun, V. M. (2024). ORFEO: Ordinal classifier and Regressor Fusion for Estimating an Ordinal categorical target. Engineering Applications of Artificial Intelligence, 133(E), 108462. https://doi.org/10.1016/j.engappai.2024.108462
    
RIS Citation
TY  - JOUR
AU  - Gómez-Orellana, Antonio Manuel
AU  - Guijo-Rubio, David
AU  - Gutiérrez, Pedro Antonio
AU  - Hervás-Martínez, César
AU  - Vargas-Yun, Víctor Manuel
DA  - 2024///
PY  - 2024
DO  - 10.1016/j.engappai.2024.108462
ID  - temp_id_334894764411
IS  - E
SP  - 108462
T2  - Engineering Applications of Artificial Intelligence
TI  - ORFEO: Ordinal classifier and Regressor Fusion for Estimating an Ordin
al categorical target
UR  - https://www.sciencedirect.com/science/article/pii/S0952197624006201?vi
a%3Dihub
VL  - 133
ER  -
    
CV Citation
A.M. Gómez-Orellana, D. Guijo-Rubio (CA), P.A. Gutiérrez, C. Hervás-Martínez, V.M. Vargas-Yun (5/5). "ORFEO: Ordinal classifier and Regressor Fusion for Estimating an Ordinal categorical target". Engineering Applications of Artificial Intelligence,  Vol. 133(E), pp. 108462, 2024. (Q1D1, IF: 8.0).