Data collection and storage capacities have increased significantly in the past decades. In order to cope with the increasingly complexity of data, feature selection methods have become an omnipresent preprocessing step ...

Intrusion detection datasets play a key role in fine tuning Intrusion Detection Systems (IDSs). Using such datasets one can distinguish between regular and anomalous behavior of a given node in the network. To build this ...

Quantitative structure–activity relationship modeling using machine learning techniques constitutes a complex computational problem, where the identification of the most informative molecular descriptors for predicting a ...

This study proposes an alternate data extraction method that combines three well-known feature selection methods for handling large and problematic datasets: the correlation-based feature selection (CFS), best first search ...

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 ...

Social media sentiment analysis consists on extracting information from users' comments. It can assist the decision-making process of companies, aid public health and security and even identify intentions and opinions about ...

Musical genre classification has been paramount in the last years, mainly in large multimedia datasets, in which new songs and genres can be added at every moment by anyone. In this context, we have seen the growing of ...

Musical genre classification has been paramount in the last years, mainly in large multimedia datasets, in which new songs and genres can be added at every moment by anyone. In this context, we have seen the growing of ...

Luminescent inorganic-organic hybrids find several applications such as in multifunctional devices or in bioimaging. In this regard, through a step-by-step process, inorganic-organic core@shell-like hybrids based on ...