Abstract—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. Many real-world applications ...

Ordinal classification refers to classification problems in which the classes have a natural order imposed on them because of the nature of the concept studied. Some ordinal classification approaches perform a projection ...

This paper approaches the problem of weed mapping for precision agriculture, using imagery provided by Unmanned Aerial Vehicles (UAVs) from sun ower and maize crops. Precision agriculture referred to weed control is ...

Nowadays, the imbalanced nature of some real-world data is receiving a lot of attention from the pattern recognition and machine learning communities in both theoretical and practical aspects, giving rise to di erent ...

Este trabajo aborda la resolución de problemas de clasificación binaria utilizando una metodología híbrida que combina la regresión logística y modelos evolutivos de redes neuronales de unidades producto. Para estimar ...

The classification of patterns into naturally ordered labels is referred to as ordinal regression. This paper proposes an ensemble methodology specifically adapted to this type of problems, which is based on computing ...

El presente trabajo es una primera aproximación a la formación de modelos de redes neuronales con unidades ocultas de tipo híbrido (sigmoides, producto) que siendo aproximadores universales, puedan utilizarse como ...

This paper proposes a time series segmentation algorithm combining a clustering technique and a genetic algorithm to automatically find segments sharing common statistical characteristics in paleoclimate time series. The ...

The strategic management of agricultural lands involves crop field monitoring each year. Crop discrimination via remote sensing is a complex task, especially if different crops have a similar spectral response and cropping ...