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12 papers · ranked by Valyu relevance

01
PPubMed12 Nov 2021
Improving the Classification of Alzheimer’s Disease Using Hybrid Gene Selection Pipeline and Deep Learning Mahendran et al. Improving the Classification of Alzheimer’s Disease
Nivedhitha Mahendran, P. M. Durai Raj Vincent, Kathiravan Srinivasan, Chuan-Yu Chang
'Chuan-Yu Chang'] Alzheimer’s is a progressive, irreversible, neurodegenerative brain disease. Even with prominent symptoms, it takes years to notice, decode, and reveal Alzheimer’s. However, advancements in technologies, such as imaging techniques, help in early diagnosis. Still, sometimes the results are inaccurate…
73relevance
02
PPubMed19 Oct 2022
Wrapper Functions for Integrating Mathematical Models into Digital Twin Event Processing
Reiner Jedermann, Walter Lang, Leopoldo Angrisani, Domenico Accardo
Analog sensors often require complex mathematical models for data analysis. Digital twins (DTs) provide platforms to display sensor data in real time but still lack generic solutions regarding how mathematical models and algorithms can be integrated. Based on previous tests for monitoring and predicting banana fruit…
73relevance
03
PPubMed18 Oct 2023
Artificial Intelligence based wrapper for high dimensional feature selection
Rahi Jain, Wei Xu
Background Feature selection is important in high dimensional data analysis. The wrapper approach is one of the ways to perform feature selection, but it is computationally intensive as it builds and evaluates models of multiple subsets of features. The existing wrapper algorithm primarily focuses on shortening the…
69relevance
04
PPubMed8 May 2025
Machine learning for Internet of Things (IoT) device identification: a comparative study
Hamid Tahaei, Anqi Liu, Hamid Forooghikian, Mehdi Gheisari + 5 more
'Faiz Zaki' 'Nor Badrul Anuar' 'Zhaoxi Fang' 'Longjun Huang' 'Vicente Alarcon-Aquino'] The rapid deployment of millions of connected devices brings significant security challenges to the Internet of Things (IoT). IoT devices are typically resource-constrained and designed for specific tasks, from which new security…
69relevance
05
PPubMed14 Apr 2023
WBM-DLNets: Wrapper-Based Metaheuristic Deep Learning Networks Feature Optimization for Enhancing Brain Tumor Detection
Muhammad Umair Ali, Shaik Javeed Hussain, Amad Zafar, Muhammad Raheel Bhutta + 2 more
This study presents wrapper-based metaheuristic deep learning networks (WBM-DLNets) feature optimization algorithms for brain tumor diagnosis using magnetic resonance imaging. Herein, 16 pretrained deep learning networks are used to compute the features. Eight metaheuristic optimization algorithms, namely, the marine…
68relevance
06
PPubMed24 Nov 2021
A Novel Rank Aggregation-Based Hybrid Multifilter Wrapper Feature Selection Method in Software Defect Prediction
Abdullateef O. Balogun, Shuib Basri, Saipunidzam Mahamad, Luiz Fernando Capretz + 4 more
The high dimensionality of software metric features has long been noted as a data quality problem that affects the performance of software defect prediction (SDP) models. This drawback makes it necessary to apply feature selection (FS) algorithm(s) in SDP processes. FS approaches can be categorized into three types…
68relevance
07
PPubMed19 Oct 2023
On the use of QDE-SVM for gene feature selection and cell type classification from scRNA-seq data On the use of QDE-SVM for gene feature selection and cell type classification from scRNA-seq data
Grace Yee Lin Ng, Shing Chiang Tan, Chia Sui Ong, Guanghui Liu
Cell type identification is one of the fundamental tasks in single-cell RNA sequencing (scRNA-seq) studies. It is a key step to facilitate downstream interpretations such as differential expression, trajectory inference, etc. scRNA-seq data contains technical variations that could affect the interpretation of the cell…
67relevance
08
PPubMed18 Dec 2023
Analyzing the impact of feature selection methods on machine learning algorithms for heart disease prediction
Zeinab Noroozi, Azam Orooji, Leila Erfannia
The present study examines the role of feature selection methods in optimizing machine learning algorithms for predicting heart disease. The Cleveland Heart disease dataset with sixteen feature selection techniques in three categories of filter, wrapper, and evolutionary were used. Then seven algorithms Bayes net…
66relevance
09
PPubMed11 Dec 2025
A multiple filter-wrapper feature selection algorithm based on process optimization mechanism for high-dimensional omics data analysis A new hybrid feature selection algorithm for high-dimensional omics data analysis
Yongtao Shi, Yuefeng Zheng, Xiaotong Bai, Elnaz Pashaei
Recently, hybrid feature selection methods have demonstrated excellent performance on high-dimensional data, but many of these methods tend to yield relatively homogeneous feature subsets. To address this, we propose a novel hybrid feature selection algorithm called the Hybrid Multiple Filter-Wrapper algorithm. This…
66relevance
10
PPubMed5 Oct 2022
Benchmark study of feature selection strategies for multi-omics data
Yingxia Li, Ulrich Mansmann, Shangming Du, Roman Hornung
Background In the last few years, multi-omics data, that is, datasets containing different types of high-dimensional molecular variables for the same samples, have become increasingly available. To date, several comparison studies focused on feature selection methods for omics data, but to our knowledge, none compared…
65relevance
11
PPubMed9 Sep 2023
Nested ensemble selection: An effective hybrid feature selection method
Firuz Kamalov, Hana Sulieman, Sherif Moussa, Jorge Avante Reyes + 1 more
'Murodbek Safaraliev'] It has been shown that while feature selection algorithms are able to distinguish between relevant and irrelevant features, they fail to differentiate between relevant and redundant and correlated features. To address this issue, we propose a highly effective approach, called Nested Ensemble…
65relevance
12
PPubMed9 Mar 2023
Control and Measurement Systems Supporting the Production of Haylage in Baler-Wrapper Machines
Michał Zawada, Mateusz Nijak, Jarosław Mac, Jan Szczepaniak + 11 more
'Stanisław Legutko' 'Julia Gościańska-Łowińska' 'Sebastian Szymczyk' 'Michał Kaźmierczak' 'Mikołaj Zwierzyński' 'Jacek Wojciechowski' 'Tomasz Szulc' 'Roman Rogacki' 'José Miguel Molina Martínez' 'Dolores Parras-Burgos' 'Daniel García Fernández-Pacheco'] Baler-wrappers are machines designed to produce high-quality…
62relevance

Results for wrapper method

Improving the Classification of Alzheimer’s Disease Using Hybrid Gene Selection Pipeline and Deep Learning Mahendran et al. Improving the Classification of Alzheimer’s Disease

Wrapper Functions for Integrating Mathematical Models into Digital Twin Event Processing

Artificial Intelligence based wrapper for high dimensional feature selection

Machine learning for Internet of Things (IoT) device identification: a comparative study

WBM-DLNets: Wrapper-Based Metaheuristic Deep Learning Networks Feature Optimization for Enhancing Brain Tumor Detection

A Novel Rank Aggregation-Based Hybrid Multifilter Wrapper Feature Selection Method in Software Defect Prediction

On the use of QDE-SVM for gene feature selection and cell type classification from scRNA-seq data On the use of QDE-SVM for gene feature selection and cell type classification from scRNA-seq data

Analyzing the impact of feature selection methods on machine learning algorithms for heart disease prediction

A multiple filter-wrapper feature selection algorithm based on process optimization mechanism for high-dimensional omics data analysis A new hybrid feature selection algorithm for high-dimensional omics data analysis

Benchmark study of feature selection strategies for multi-omics data

Nested ensemble selection: An effective hybrid feature selection method

Control and Measurement Systems Supporting the Production of Haylage in Baler-Wrapper Machines

Improving the Classification of Alzheimer’s Disease Using Hybrid Gene Selection Pipeline and Deep Learning Mahendran et al. Improving the Classification of Alzheimer’s Disease

Wrapper Functions for Integrating Mathematical Models into Digital Twin Event Processing

Artificial Intelligence based wrapper for high dimensional feature selection

Machine learning for Internet of Things (IoT) device identification: a comparative study

WBM-DLNets: Wrapper-Based Metaheuristic Deep Learning Networks Feature Optimization for Enhancing Brain Tumor Detection

A Novel Rank Aggregation-Based Hybrid Multifilter Wrapper Feature Selection Method in Software Defect Prediction

On the use of QDE-SVM for gene feature selection and cell type classification from scRNA-seq data On the use of QDE-SVM for gene feature selection and cell type classification from scRNA-seq data

Analyzing the impact of feature selection methods on machine learning algorithms for heart disease prediction

A multiple filter-wrapper feature selection algorithm based on process optimization mechanism for high-dimensional omics data analysis A new hybrid feature selection algorithm for high-dimensional omics data analysis

Benchmark study of feature selection strategies for multi-omics data

Nested ensemble selection: An effective hybrid feature selection method

Control and Measurement Systems Supporting the Production of Haylage in Baler-Wrapper Machines