Gramian angular and markov transition fields applied to time series ordinal classification
V. Vargas, R. Ayllón-Gavilán , A. Durán-Rosal, P. Gutiérrez, C. Hervás-Martínez, D. Guijo-Rubio
International work-conference on artificial neural networks, pp. 505-516, 2023Abstract
This work presents a novel ordinal Deep Learning (DL) approach to Time Series Ordinal Classification (TSOC) field. TSOC consists in classifying time series with labels showing a natural order between them. This particular property of the output variable should be exploited to boost the performance for a given problem. This paper presents a novel DL approach in which time series are encoded as 3-channels images using Gramian Angular Field and Markov Transition Field. A soft labelling approach, which considers the probabilities generated by a unimodal distribution for obtaining soft labels that replace crisp labels in the loss function, is applied to a ResNet18 model. Specifically, beta and triangular distributions have been applied. They have been compared against three state-of-the-art deep learners in the Time Series Classification (TSC) field using 13 univariate and multivariate time series datasets. The approach considering the triangular distribution (O-GAMTF) outperforms all the techniques benchmarked.
Cite this publication
BibTex
@inproceedings{vargas2023gramian,
author = {Víctor Manuel Vargas and Rafael Ayllón-Gavilán and Antonio Manuel Durán-Rosal and Pedro Antonio Gutiérrez and César Hervás-Martínez and David Guijo-Rubio},
title = {Gramian angular and markov transition fields applied to time series ordinal classification},
booktitle = {International work-conference on artificial neural networks},
year = {2023},
pages = {505--516},
doi = {10.1007/978-3-031-43078-7_41}
}
APA
Vargas, V., Ayllón-Gavilán, R., Durán-Rosal, A., Gutiérrez, P., Hervás-Martínez, C., Guijo-Rubio, D. (2023). Gramian angular and markov transition fields applied to time series ordinal classification. In International work-conference on artificial neural networks (pp. 505-516).
CV
V.M. Vargas, R. Ayllón-Gavilán (CA), A.M. Durán-Rosal, P.A. Gutiérrez, C. Hervás-Martínez, D. Guijo-Rubio, (1/6) "Gramian angular and markov transition fields applied to time series ordinal classification". International work-conference on artificial neural networks, pp. 505-516, 2023.
RIS
TY - CONF T1 - Gramian angular and markov transition fields applied to time series ordinal classification T2 - International work-conference on artificial neural networks AU - Vargas, Víctor Manuel AU - Ayllón-Gavilán, Rafael AU - Durán-Rosal, Antonio Manuel AU - Gutiérrez, Pedro Antonio AU - Hervás-Martínez, César AU - Guijo-Rubio, David JO - International work-conference on artificial neural networks JA - International work-conference on artificial neural networks Y1 - 2023 PY - 2023 SP - 505 EP - 516 DO - 10.1007/978-3-031-43078-7_41 ER -