11 citations · 18 across the 9 of their papers we have counts for
9 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…
From Kellgren-Lawrence to Calcium Pyrophosphate Crystal Deposition: A Soft-Labelling Framework for Knee Osteoarthritis Assessmen
Francisco Bérchez-Moreno, Riccardo Rosati, Maria Chiara Fiorentino +6
Background and objective. Conventional Deep Learning (DL) approaches for Knee Osteoarthritis (KOA) grading rely on one-hot labels, which fail to capture both the ordinal uncertaint…
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…
Improving the classification of extreme classes by means of loss regularisation and generalised beta distributions
Víctor Manuel Vargas, Pedro Antonio Gutiérrez, Javier Barbero-Gómez +1
An ordinal classification problem is one in which the target variable takes values on an ordinal scale. Nowadays, there are many of these problems associated with real-world tasks…
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…