Deep Ordinal Classification Based on the Proportional Odds Model

Authors

Víctor Manuel Vargas-Yun

Pedro Antonio Gutiérrez

César Hervás-Martínez

Conference Proceedings

Proceedings of the international work-conference on the interplay between natural and artificial computation (IWINAC 2019)

ISBN 978-3-030-19650-9

Vol. 11487

Pages 441-451

Abstract

This paper proposes a deep neural network model for ordinal regression problems based on the use of a probabilistic ordinal link function in the output layer. This link function reproduces the Proportional Odds Model (POM), a statistical linear model which projects each pattern into a 1-dimensional space. In our case, the projection is estimated by a non-linear deep neural network. After that, patterns are classified using a set of ordered thresholds. In order to further improve the results, we combine this link function with a loss cost that takes the distance between classes into account, based on the weighted Kappa index. The experiments are based on two ordinal classification problems, and the statistical tests confirm that our ordinal network outperforms the nominal version and other proposals considered in the literature.

Keywords

convolutional neural network deep learning ordinal classification ordinal regression proportional odds model

BibTex Citation

@inproceedings{Vargas2019Deep,
	author = {Vargas-Yun, V{\' i}ctor Manuel and Guti{\' e}rrez, Pedro Antonio and Herv{\' a}s-Mart{\' i}nez, C{\' e}sar},
	booktitle = {Proceedings of the international work-conference on the interplay between natural and artificial computation ({IWINAC} 2019)},
	doi = {10.1007/978-3-030-19651-6_43},
	year = {2019},
	pages = {441--451},
	title = {Deep {Ordinal} {Classification} {Based} on the {Proportional} {Odds} {Model}},
	url = {https://doi.org/10.1007/978-3-030-19651-6_43},
	howpublished = {https://doi.org/10.1007/978-3-030-19651-6\textunderscore{}43},
	volume = {11487},
}

BibTex Unicode Citation

@inproceedings{Vargas2019Deep,
	author = {Vargas-Yun, Víctor Manuel and Gutiérrez, Pedro Antonio and Hervás-Martínez, César},
	booktitle = {Proceedings of the international work-conference on the interplay between natural and artificial computation ({IWINAC} 2019)},
	doi = {10.1007/978-3-030-19651-6_43},
	year = {2019},
	pages = {441--451},
	title = {Deep {Ordinal} {Classification} {Based} on the {Proportional} {Odds} {Model}},
	url = {https://doi.org/10.1007/978-3-030-19651-6_43},
	howpublished = {https://doi.org/10.1007/978-3-030-19651-6\textunderscore{}43},
	volume = {11487},
}

APA Citation

Vargas-Yun, V. M., Gutiérrez, P. A., & Hervás-Martínez, C. (2019). Deep Ordinal Classification Based on the Proportional Odds Model. Proceedings of the International Work-Conference on the Interplay between Natural and Artificial Computation (IWINAC 2019), 11487, 441–451. https://doi.org/10.1007/978-3-030-19651-6_43

RIS Citation

TY  - CONF
AU  - Vargas-Yun, Víctor Manuel
AU  - Gutiérrez, Pedro Antonio
AU  - Hervás-Martínez, César
C3  - Proceedings of the international work-conference on the interplay betw
een natural and artificial computation (IWINAC 2019)
DA  - 2019///
C2  - 2019
DO  - 10.1007/978-3-030-19651-6_43
ID  - temp_id_665361460221
SP  - 441-451
TI  - Deep Ordinal Classification Based on the Proportional Odds Model
UR  - https://doi.org/10.1007/978-3-030-19651-6_43
VL  - 11487
ER  -

CV Citation

V.M. Vargas-Yun (CA), P.A. Gutiérrez, C. Hervás-Martínez (1/3). "Deep Ordinal Classification Based on the Proportional Odds Model". Proceedings of the international work-conference on the interplay between natural and artificial computation (IWINAC 2019), pp. 441-451, 2019.