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Ordinal regression methods: survey and experimental study
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 ...
Selecting patterns and features for between- and within- crop-row weed mapping using UAV-imagery
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 ...
Borderline kernel based over-sampling
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 ...
Projection based ensemble learning for ordinal regression
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 ...
A Review of Classification Problems and Algorithms in Renewable Energy Applications
Classification problems and their corresponding solving approaches constitute one of the fields of machine learning. The application of classification schemes in Renewable Energy (RE) has gained significant attention in ...