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Early Prediction of Diabetes Using Feature Selection and Machine Learning Algorithms
Diabetes has become one of the most common diseases in middle- and low-income countries. Machine learning (ML) and data mining techniques have...
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Evaluating the impact of filter-based feature selection in intrusion detection systems
High dimensionality can lead to overfitting and affect the modeling power of classification algorithms, resulting an increase in false positive rate...
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MBSSA-Bi-AESN: Classification prediction of bi-directional adaptive echo state network based on modified binary salp swarm algorithm and feature selection
In the era of big data, the demand for multivariate time series prediction has surged, drawing increased attention to feature selection and neural...
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CVS-FLN: a novel IoT-IDS model based on metaheuristic feature selection and neural network classification model
The Internet of Things (IoT) is one of the technologies that will be used all over the world in the future, and its security and privacy features are...
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Enhanced Ali Baba and the forty thieves algorithm for feature selection
Feature Selection (FS) aims to ameliorate the classification rate of dataset models by selecting only a small set of appropriate features from the...
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Safety helmet detection method based on semantic guidance and feature selection fusion
Safety helmet detection is a hot topic of research in the field of industrial safety for object detection technology. Existing object detection...
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A Novel Feature Fusion Approach for Classification of Motor Imagery EEG Based on Hierarchical Extreme Learning Machine
Because feature extraction from electroencephalogram (EEG) signals is essential for cognitive investigations, effective feature extraction approaches...
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HMOSHSSA: a novel framework for solving simultaneous clustering and feature selection problems
In real-life scenarios, information about the number of clusters is unknown. Due to this, clustering algorithms are unable to generate the valuable...
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Automatic Diagnosis of Autism Spectrum Disorder Detection Using a Hybrid Feature Selection Model with Graph Convolution Network
A neurodevelopmental disorder is called an autism spectrum disorder (ASD) that influences a person’s assertion, interaction, and learning abilities....
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An Empirical Evaluation of Constrained Feature Selection
While feature selection helps to get smaller and more understandable prediction models, most existing feature-selection techniques do not consider...
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Semi-supervised attack detection in industrial control systems with deviation networks and feature selection
With the rapid development of Industry 4.0, the importance of cyber security for industrial control systems has become increasingly prominent. The...
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Content-Aware Hierarchical Representation Selection for Cross-View Geo-Localization
Cross-view geo-localization (CVGL) aims to retrieve the images that contain the same geographic target content and are from different views. However,...
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Membership Weight Salp Swarm Algorithm (MWSSA) based feature selection and deep learning approach for breast cancer classification of SNP genomics data
Single Nucleotide Polymorphisms refer to variations in individual Deoxyribonucleic Acid bases, serving as potential clinical phenoty** markers....
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An approach of a quantum-inspired document ranking algorithm by using feature selection methodology
The main goal of an information retrieval system (IR) is ranking. Several methodologies were adopted with the integration of computing and advanced...
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Feature Selection for Hierarchical Multi-label Classification
In this work we study how conventional feature selection methods can be applied to Hierarchical Multi-label Classification Problems. In Hierarchical...
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3FS-CBR-IRF: improving case retrieval for case-based reasoning with three feature selection and improved random forest
Case-based reasoning (CBR) is widely used in medical decision support systems because of its similarity to human reasoning. Despite the effectiveness...
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Model selection in reconciling hierarchical time series
Model selection has been proven an effective strategy for improving accuracy in time series forecasting applications. However, when dealing with...
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Incremental feature selection approach to multi-dimensional variation based on matrix dominance conditional entropy for ordered data set
Rough set theory is a mathematical tool widely employed in various fields to handle uncertainty. Feature selection, as an essential and independent...
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Unsupervised feature selection based on incremental forward iterative Laplacian score
Feature selection facilitates intelligent information processing, and the unsupervised learning of feature selection has become important. In terms...
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Fusion Based Feature Extraction and Optimal Feature Selection in Remote Sensing Image Retrieval
In remote sensing (RS) community, RSIR (Remote Sensing Image Retrieval) is considered as a tough topic and gained more attention because the data is...
