57 citations · 104 across the 11 of their papers we have counts for
11 papers
ADABORD: a novel AdaBoost approach for ordinal classification
Rafael Ayllón-Gavilán, Francisco José Martínez-Estudillo, David Guijo-Rubio +2
Ordinal Classification (OC) deals with classification tasks where the classes follow a natural order. Despite the progress in OC, many existing approaches fail to fully leverage th…
A novel ordinal multi-view aggregation scheme for oak defoliation
Francisco Bérchez-Moreno, Ricardo Enrique Hernández-Lambraño, David Guijo-Rubio +4
Forest decline driven by climate and biotic stressors threatens ecosystem functioning, making accurate monitoring of tree health essential. In this work, we address tree defoliatio…
TOC-UCO: a comprehensive repository of tabular ordinal classification datasets
Rafael Ayllón-Gavilán, David Guijo-Rubio, Antonio Manuel Gómez-Orellana +3
An ordinal classification (OC) problem corresponds to a special type of classification characterised by the presence of a natural order relationship among the classes. This type of…
Splitting criteria for ordinal decision trees: an experimental study
Rafael Ayllón-Gavilán, Francisco José Martínez-Estudillo, David Guijo-Rubio +2
Ordinal Classification (OC) addresses those classification tasks where the labels exhibit a natural order. Unlike nominal classification, which treats all classes as mutually exclu…
dlordinal: a Python package for deep ordinal classification
Francisco Bérchez-Moreno, Víctor M. Vargas, Rafael Ayllón-Gavilán +4
dlordinal is a new Python library that unifies many recent deep ordinal classification methodologies available in the literature. Developed using PyTorch as underlying framework, i…
aeon: a Python toolkit for learning from time series
Matthew Middlehurst, Ali Ismail-Fawaz, Antoine Guillaume +8
aeon is a unified Python 3 library for all machine learning tasks involving time series. The package contains modules for time series forecasting, classification, extrinsic regress…
Validation of artificial neural networks to model the acoustic behaviour of induction motors
F. J. Jimenez-Romero, D. Guijo-Rubio, F. R. Lara-Raya +2
In the last decade, the sound quality of electric induction motors is a hot topic in the research field. Specially, due to its high number of applications, the population is expose…
Convolutional and Deep Learning based techniques for Time Series Ordinal Classification
Rafael Ayllón-Gavilán, David Guijo-Rubio, Pedro Antonio Gutiérrez +2
Time Series Classification (TSC) covers the supervised learning problem where input data is provided in the form of series of values observed through repeated measurements over tim…
A Dictionary-based approach to Time Series Ordinal Classification
Rafael Ayllón-Gavilán, David Guijo-Rubio, Pedro Antonio Gutiérrez +1
Time Series Classification (TSC) is an extensively researched field from which a broad range of real-world problems can be addressed obtaining excellent results. One sort of the ap…
Unsupervised Feature Based Algorithms for Time Series Extrinsic Regression
David Guijo-Rubio, Matthew Middlehurst, Guilherme Arcencio +2
Time Series Extrinsic Regression (TSER) involves using a set of training time series to form a predictive model of a continuous response variable that is not directly related to th…
Time series clustering based on the characterisation of segment typologies
David Guijo-Rubio, Antonio Manuel Durán-Rosal, Pedro Antonio Gutiérrez +2
Time series clustering is the process of grouping time series with respect to their similarity or characteristics. Previous approaches usually combine a specific distance measure f…