With the advent of high dimensionality, adequate identification of relevant features of the
data has become indispensable in real-world scenarios. In this context, the importance of …

This paper offers a comprehensive approach to feature selection in the scope of
classification problems, explaining the foundations, real application problems and the …

In this paper a new framework for feature selection consisting of an ensemble of filters and
classifiers is described. Five filters, based on different metrics, were employed. Each filter …

Breast cancer is the most common cancer diagnosed and cause of death among women
worldwide. There is evidence that early detection and treatment can increase the survival …

Feature selection aims to select strongly relevant features and discard the rest. Recently,
embedded feature selection methods, which incorporate feature weights learning into the …

In this paper, we present a new method for few-sample supervised feature selection (FS).
Our method first learns the manifold of the feature space of each class using kernels …

The task of choosing the appropriate classifier for a given scenario is not an easy-to-solve
question. First, there is an increasingly high number of algorithms available belonging to …

Human immunodeficiency virus 1 (HIV-1) protease (PR) plays a crucial role in the
maturation of the virus. The study of substrate specificity of HIV-1 PR as a new endeavor …

The advances of high-throughput biotechnologies have shifted the focus of biomedical
science from studying individual molecules towards analysing the interactions of the …

In this review, PubMed database has been explored to elucidate the problems related to
HIV/AIDS, which have been solved previously using various machine learning approaches …