Microarray technology has become an emerging trend in the domain of genetic research in
which many researchers employ to study and investigate the levels of genes' expression in a …

This survey aims at providing a state-of-the-art overview of feature selection and fusion
strategies, which select and combine multi-view features effectively to accomplish …

Practical real-world scenarios such as the Internet, social networks, and biological networks
present the challenges of data scarcity and complex correlations, which limit the applications …

Unsupervised band selection aims to select informative spectral bands to preprocess
hyperspectral images (HSIs) without using labels. Traditional band selection methods only …

Feature selection is an important step in building classifiers for high-dimensional data
problems, such as EEG classification for BCI applications. This paper proposes a new …

Background Feature selection, as a preprocessing stage, is a challenging problem in
various sciences such as biology, engineering, computer science, and other fields. For this …

Feature selection has been an outstanding strategy in eliminating redundant and inefficient
features in high-dimensional data. This paper introduces a novel unsupervised feature …

In real-world applications, data instances are not only related to high-dimensional features,
but also interconnected with each other. However, the interconnection information has not …

Feature selection can reduce the dimension of data and select the representative features.
The available researches have shown that the underlying geometric structures of both the …

Accurately ranking images and multimedia objects are of paramount relevance in many
retrieval and learning tasks. Manifold learning methods have been investigated for ranking …