Review of swarm intelligence-based feature selection methods
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TLDR
A comparative analysis of different feature selection methods is presented, and a general categorization of these methods is performed, which shows the strengths and weaknesses of the different studied swarm intelligence-based feature selection Methods.About:
This article is published in Engineering Applications of Artificial Intelligence.The article was published on 2021-04-01 and is currently open access. It has received 200 citations till now. The article focuses on the topics: Dimensionality reduction & Feature selection.read more
Citations
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Feature dimensionality reduction: a review
TL;DR: In this paper , two-dimensional reduction methods, feature selection and feature extraction, are introduced; the current mainstream dimensionality reduction algorithms are analyzed, including the method for small sample and method based on deep learning.
Journal ArticleDOI
Enhanced whale optimization algorithm for medical feature selection: A COVID-19 case study
TL;DR: Wang et al. as discussed by the authors proposed an enhanced whale optimization algorithm named E-WOA using a pooling mechanism and three effective search strategies named migrating, preferential selecting, and enriched encircling prey.
Journal ArticleDOI
Feature dimensionality reduction: a review
TL;DR: In this paper , two-dimensional reduction methods, feature selection and feature extraction, are introduced; the current mainstream dimensionality reduction algorithms are analyzed, including the method for small sample and method based on deep learning.
Journal ArticleDOI
Presentation a Trust Walker for rating prediction in recommender system with Biased Random Walk: Effects of H-index centrality, similarity in items and friends
TL;DR: A trust-based recommender system is presented that predicts the score of items that the target user has not rated, and if the item is not found, it offers the user the items dependent on that item that are also part of the user's interests.
Journal ArticleDOI
Gene selection for microarray data classification via multi-objective graph theoretic-based method
TL;DR: In this paper , a novel social network analysis-based gene selection approach is proposed, which has two main objectives of the relevance maximization and redundancy minimization of the selected genes.
References
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Journal ArticleDOI
The WEKA data mining software: an update
TL;DR: This paper provides an introduction to the WEKA workbench, reviews the history of the project, and, in light of the recent 3.6 stable release, briefly discusses what has been added since the last stable version (Weka 3.4) released in 2003.
Journal ArticleDOI
Particle swarm optimization
TL;DR: A snapshot of particle swarming from the authors’ perspective, including variations in the algorithm, current and ongoing research, applications and open problems, is included.
Journal ArticleDOI
Grey Wolf Optimizer
TL;DR: The results of the classical engineering design problems and real application prove that the proposed GWO algorithm is applicable to challenging problems with unknown search spaces.
Journal ArticleDOI
Feature selection based on mutual information criteria of max-dependency, max-relevance, and min-redundancy
TL;DR: In this article, the maximal statistical dependency criterion based on mutual information (mRMR) was proposed to select good features according to the maximal dependency condition. But the problem of feature selection is not solved by directly implementing mRMR.
Journal ArticleDOI
Machine learning in automated text categorization
TL;DR: This survey discusses the main approaches to text categorization that fall within the machine learning paradigm and discusses in detail issues pertaining to three different problems, namely, document representation, classifier construction, and classifier evaluation.
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