[HTML][HTML] Microarray cancer feature selection: Review, challenges and research directions

MA Hambali, TO Oladele, KS Adewole - International Journal of Cognitive …, 2020‏ - Elsevier
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 …

Feature selection with multi-view data: A survey

R Zhang, F Nie, X Li, X Wei - Information Fusion, 2019‏ - Elsevier
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 …

A survey on feature selection

J Miao, L Niu - Procedia computer science, 2016‏ - Elsevier
Feature selection, as a dimensionality reduction technique, aims to choosing a small subset
of the relevant features from the original features by removing irrelevant, redundant or noisy …

A survey on hybrid feature selection methods in microarray gene expression data for cancer classification

N Almugren, H Alshamlan - IEEE access, 2019‏ - ieeexplore.ieee.org
The emergence of DNA Microarray technology has enabled researchers to analyze the
expression level of thousands of genes simultaneously. The Microarray data analysis is the …

[HTML][HTML] EMG feature selection and classification using a Pbest-guide binary particle swarm optimization

J Too, AR Abdullah, N Mohd Saad, W Tee - Computation, 2019‏ - mdpi.com
Due to the increment in hand motion types, electromyography (EMG) features are
increasingly required for accurate EMG signals classification. However, increasing in the …

Robust structured subspace learning for data representation

Z Li, J Liu, J Tang, H Lu - IEEE transactions on pattern analysis …, 2015‏ - ieeexplore.ieee.org
To uncover an appropriate latent subspace for data representation, in this paper we propose
a novel Robust Structured Subspace Learning (RSSL) algorithm by integrating image …

An IoT-enabled stroke rehabilitation system based on smart wearable armband and machine learning

G Yang, J Deng, G Pang, H Zhang, J Li… - IEEE journal of …, 2018‏ - ieeexplore.ieee.org
Surface electromyography signal plays an important role in hand function recovery training.
In this paper, an IoT-enabled stroke rehabilitation system was introduced which was based …

Adaptive unsupervised feature selection with structure regularization

M Luo, F Nie, X Chang, Y Yang… - IEEE transactions on …, 2017‏ - ieeexplore.ieee.org
Feature selection is one of the most important dimension reduction techniques for its
efficiency and interpretation. Since practical data in large scale are usually collected without …

A possibilistic information fusion-based unsupervised feature selection method using information quality measures

P Zhang, T Li, Z Yuan, Z Deng, G Wang… - … on Fuzzy Systems, 2023‏ - ieeexplore.ieee.org
The main goal of most information quality (IQ)-based measures is to combine data provided
by multiple information sources to enhance the quality of information essential for decision …

Clustering-guided sparse structural learning for unsupervised feature selection

Z Li, J Liu, Y Yang, X Zhou, H Lu - IEEE Transactions on …, 2013‏ - ieeexplore.ieee.org
Many pattern analysis and data mining problems have witnessed high-dimensional data
represented by a large number of features, which are often redundant and noisy. Feature …