An exploratory analysis of data noisy scenarios in a Pareto-front based dynamic feature selection method-Reference-Cited by-同舟云学术

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An exploratory analysis of data noisy scenarios in a Pareto-front based dynamic feature selection method

Published:2021-03 Issue: Volume:100 Page:106951
ISSN:1568-4946
Container-title:Applied Soft Computing
language:en
Short-container-title:Applied Soft Computing

Author:

Jesus Jhoseph,Canuto Anne,Araújo Daniel

Funder

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Publisher

Elsevier BV

Subject

Software

Reference49 articles.

1. Challenges of feature selection for big data analytics;Li;IEEE Intell. Syst.,2017

2. Computational Methods of Feature Selection;Liu,2007

3. A survey on feature selection methods;Chandrashekar;Comput. Electr. Eng.,2014

4. An introduction to variable and feature selection;Guyon;J. Mach. Learn. Res.,2003

5. Effective global approaches for mutual information based feature selection;Nguyen,2014

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1. Towards Total Dynamicity of a Feature Selection Method based on the Pareto Front;2024 International Joint Conference on Neural Networks (IJCNN);2024-06-30

2. Feature Drift Aware for Intrusion Detection System Using Developed Variable Length Particle Swarm Optimization in Data Stream;IEEE Access;2023

3. A New Feature Selection Method Based on a Self-Variant Genetic Algorithm Applied to Android Malware Detection;Symmetry;2021-07-18

4. A Feature Selection Method by using Chaotic Cuckoo Search Optimization Algorithm with Elitist Preservation and Uniform Mutation for Data Classification;Discrete Dynamics in Nature and Society;2021-06-18

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