11 citations · 18 across the 6 of their papers we have counts for
6 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…
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…
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…