The problem of feature selection has been paramount in the last years, since it can be as important as the classification step itself. The main goal of feature selection is to find out the subset of features that optimize ...

Although non-technical losses automatic identification has been massively studied, the problem of selecting the most representative features in order to boost the identification accuracy has not attracted much attention ...

Although non-technical losses automatic identification has been massively studied, the problem of selecting the most representative features in order to boost the identification accuracy has not attracted much attention ...

Feature selection, an important combinatorial optimization problem in data mining, aims to find a reduced subset of features of high quality in a dataset. Different categories of importance measures can be used to estimate ...

Feature selection aims to find the most important information from a given set of features. As this task can be seen as an optimization problem, the combinatorial growth of the possible solutions may be in-viable for a ...

Feature selection aims to find the most important information from a given set of features. As this task can be seen as an optimization problem, the combinatorial growth of the possible solutions may be in-viable for a ...

Although sound classification in soundscape studies are generally performed by experts, the large growth of acoustic data presents a major challenge for performing such task. At the same time, the identification of more ...

Functional Data Analysis (FDA) has become a very important eld in recent years due to its wide range of applications. However, there are several real-life applications in which hybrid functional data appear, i.e., data ...