Abstract Operations Research (OR) and Artificial Intelligence (AI) disciplines have been
playing major roles on the design of new intelligent systems. Recently, different contributions …

Ordinal regression problems are those machine learning problems where the objective is to
classify patterns using a categorical scale which shows a natural order between the labels …

In ordinal classification problems, the class value exhibits a natural order. Usually, these
problems are solved as multiclass classification problems while discarding the ordering form …

ABSTRACT A learning‐by‐example algorithm, the ordinal learning model (OLM), that
automatically generates symbolic rule‐bases from examples was applied to four real‐world …

Ordinal decision problems are very common in real-life. As a result, ordinal classification
models have drawn much attention in recent years. Many ordinal problem domains assume …

In recent years, a number of machine learning algorithms have been developed for the
problem of ordinal classification. These algorithms try to exploit, in one way or the other, the …

Although ranking (ordinal classification/regression) based on criteria is related closely to
classification based on attributes, the development of methods for learning a ranking on the …

While ordinal classification problems are common in many situations, induction of ordinal
decision trees has not evolved significantly. Conventional trees for regression settings or …

Classification problems involve the assignment of a discrete set of alternatives described
over some criteria into predefined groups. This paper is focused on the case where the …

Ordinal classification or ordinal regression is a classification problem in which the labels
have an ordered arrangement between them. Due to this order, alternative performance …