Classification with imbalanced datasets supposes a new challenge for researches in the
framework of machine learning. This problem appears when the number of patterns that …

This paper proposes a multiclassification algorithm using multilayer perceptron neural
network models. It tries to boost two conflicting main objectives of multiclassifiers: a high …

Deep Neural Networks are actively being used in the design of autonomous Cyber-Physical
Systems (CPSs). The advantage of these models is their ability to handle high-dimensional …

One of the objectives of conservation agriculture to reduce soil erosion in olive orchards is to
protect the soil with cover crops between rows. Andalusian and European administrations …

Recently, a multi-objective Sensitivity–Accuracy based methodology has been proposed for
building classifiers for multi-class problems. This technique is especially suitable for …

In this paper, a dynamic over-sampling procedure is proposed to improve the classification
of imbalanced datasets with more than two classes. This procedure is incorporated into a …

Accuracy alone can be deceptive when evaluating the performance of a classifier, especially
if the problem involves a high number of classes. This paper proposes an approach used for …

Abstract Cyber-Physical Systems (CPSs) are ubiquitous through our interactions with
applications such as smart homes, medical devices, avionics, and automobiles. However …

The machine learning community has traditionally used correct classification rates or
accuracy (C) values to measure classifier performance and has generally avoided …

Accuracy alone is insufficient to evaluate the performance of a classifier especially when the
number of classes increases. This paper proposes an approach to deal with multi-class …