A tutorial on variable selection for clinical prediction models: feature selection methods in data mining could improve the results

F Bagherzadeh-Khiabani, A Ramezankhani… - Journal of clinical …, 2016 - Elsevier
Objectives Identifying an appropriate set of predictors for the outcome of interest is a major
challenge in clinical prediction research. The aim of this study was to show the application of …

[HTML][HTML] Network traffic classification for data fusion: A survey

J Zhao, X **g, Z Yan, W Pedrycz - Information Fusion, 2021 - Elsevier
Traffic classification groups similar or related traffic data, which is one main stream
technique of data fusion in the field of network management and security. With the rapid …

Feature selection based on structured sparsity: A comprehensive study

J Gui, Z Sun, S Ji, D Tao, T Tan - IEEE transactions on neural …, 2016 - ieeexplore.ieee.org
Feature selection (FS) is an important component of many pattern recognition tasks. In these
tasks, one is often confronted with very high-dimensional data. FS algorithms are designed …

Discriminative least squares regression for multiclass classification and feature selection

S **ang, F Nie, G Meng, C Pan… - IEEE transactions on …, 2012 - ieeexplore.ieee.org
This paper presents a framework of discriminative least squares regression (LSR) for
multiclass classification and feature selection. The core idea is to enlarge the distance …

Prospect of using artificial intelligence for microwave nondestructive testing technique: A review

NHMM Shrifan, MF Akbar, NAM Isa - IEEE Access, 2019 - ieeexplore.ieee.org
The development in materials technology has produced stronger, lighter, stiffer, and more
durable electrically insulating composites which are replacing metals in many applications …

A machine-learning framework for predicting multiple air pollutants' concentrations via multi-target regression and feature selection

S Masmoudi, H Elghazel, D Taieb, O Yazar… - Science of the Total …, 2020 - Elsevier
Air pollution is considered one of the biggest threats for the ecological system and human
existence. Therefore, air quality monitoring has become a necessity in urban and industrial …

Classifier and feature set ensembles for web page classification

A Onan - Journal of Information Science, 2016 - journals.sagepub.com
Web page classification is an important research direction on web mining. The abundant
amount of data available on the web makes it essential to develop efficient and robust …

Long-term performance analysis and power prediction of PV technology in the State of Qatar

F Touati, NA Chowdhury, K Benhmed… - Renewable Energy, 2017 - Elsevier
Abstract “Solar photovoltaic (PV) energy in GCC”-the term seems convincing to many solar
PV industries due to high solar exposure in GCC region. However, long-term effects such as …

[HTML][HTML] Imbalanced data fault diagnosis method for nuclear power plants based on convolutional variational autoencoding Wasserstein generative adversarial …

J Guo, Y Wang, X Sun, S Liu, B Du - Nuclear Engineering and Technology, 2024 - Elsevier
Data-driven fault diagnosis techniques are significant for the stable operation of nuclear
power plants (NPPs). However, in practical applications, the fault diagnosis of NPPs usually …

Combinations of feature selection and machine learning algorithms for object-oriented betel palms and mango plantations classification based on Gaofen-2 imagery

H Luo, M Li, S Dai, H Li, Y Li, Y Hu, Q Zheng, X Yu… - Remote Sensing, 2022 - mdpi.com
Betel palms and mango plantations are two crucial commercial crops in tropical agricultural
areas. Accurate spatial distributions of these two crops are essential in tropical agricultural …