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Evolving Feature Selection

Authors:

Edward R. Dougherty,

Jennifer G. Dy,

Michael Berens,

George FormanAuthors Info & Claims

IEEE Intelligent Systems, Volume 20, Issue 6

Pages 64 - 76

https://doi.org/10.1109/MIS.2005.105

Published: 01 November 2005 Publication History

Abstract

Feature selection is a preprocessing technique, commonly used on high-dimensional data, that studies how to select a subset or list of attributes or variables that are used to construct models describing data. Wide data sets, which have a huge number of features but relatively few instances, introduce a novel challenge to feature selection. This installment of Trends & Controversies looks at several different ways of meeting this challenge.This department is part of a special issue on Data Mining in Bioinformatics.

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Cited By

Barra SCarta SGiuliani APisu APodda ARiboni D(2022)FootApp: An AI-powered system for football match annotationMultimedia Tools and Applications10.1007/s11042-022-13359-082:4(5547-5567)Online publication date: 4-Jul-2022
https://dl.acm.org/doi/10.1007/s11042-022-13359-0
Mallenahalli NSarma T(2018)A Tunable Particle Swarm Size Optimization Algorithm for Feature Selection2018 IEEE Congress on Evolutionary Computation (CEC)10.1109/CEC.2018.8477694(1-7)Online publication date: 8-Jul-2018
https://dl.acm.org/doi/10.1109/CEC.2018.8477694
An SWang JWei JYang ZLim EWinslett MSanderson MFu ASun JCulpepper SLo EHo JDonato DAgrawal RZheng YCastillo CSun ATseng VLi C(2017)Unsupervised Feature Selection with Joint Clustering AnalysisProceedings of the 2017 ACM on Conference on Information and Knowledge Management10.1145/3132847.3132999(1639-1648)Online publication date: 6-Nov-2017
https://dl.acm.org/doi/10.1145/3132847.3132999
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Index Terms

Evolving Feature Selection
1. Applied computing
  1. Life and medical sciences
2. Computing methodologies
  1. Machine learning
    1. Learning paradigms
      1. Unsupervised learning
        Cluster analysis
    2. Machine learning algorithms
      1. Feature selection

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Information & Contributors

Information

Published In

cover image IEEE Intelligent Systems

IEEE Intelligent Systems Volume 20, Issue 6

November 2005

92 pages

ISSN:1541-1672

Issue’s Table of Contents

Copyright © 2006.

Publisher

IEEE Educational Activities Department

United States

Publication History

Published: 01 November 2005

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Cited By

Barra SCarta SGiuliani APisu APodda ARiboni D(2022)FootApp: An AI-powered system for football match annotationMultimedia Tools and Applications10.1007/s11042-022-13359-082:4(5547-5567)Online publication date: 4-Jul-2022
https://dl.acm.org/doi/10.1007/s11042-022-13359-0
Mallenahalli NSarma T(2018)A Tunable Particle Swarm Size Optimization Algorithm for Feature Selection2018 IEEE Congress on Evolutionary Computation (CEC)10.1109/CEC.2018.8477694(1-7)Online publication date: 8-Jul-2018
https://dl.acm.org/doi/10.1109/CEC.2018.8477694
An SWang JWei JYang ZLim EWinslett MSanderson MFu ASun JCulpepper SLo EHo JDonato DAgrawal RZheng YCastillo CSun ATseng VLi C(2017)Unsupervised Feature Selection with Joint Clustering AnalysisProceedings of the 2017 ACM on Conference on Information and Knowledge Management10.1145/3132847.3132999(1639-1648)Online publication date: 6-Nov-2017
https://dl.acm.org/doi/10.1145/3132847.3132999
Izetta JVerdes PGranitto P(2017)Improved multiclass feature selection via list combinationExpert Systems with Applications: An International Journal10.1016/j.eswa.2017.06.04388:C(205-216)Online publication date: 1-Dec-2017
https://dl.acm.org/doi/10.1016/j.eswa.2017.06.043
Moro SCortez PRita P(2017)A framework for increasing the value of predictive data-driven models by enriching problem domain characterization with novel featuresNeural Computing and Applications10.1007/s00521-015-2157-828:6(1515-1523)Online publication date: 1-Jun-2017
https://dl.acm.org/doi/10.1007/s00521-015-2157-8
Simonson KDerek West RHansen RLaBruyere TVan Benthem M(2017)A statistical approach to combining multisource information in one-class classifiersStatistical Analysis and Data Mining10.1002/sam.1134210:4(199-210)Online publication date: 1-Aug-2017
https://dl.acm.org/doi/10.1002/sam.11342
Bafna PShirwaikar SPramod D(2016)Multi-Step Iterative Algorithm for Feature Selection on Dynamic DocumentsInternational Journal of Information Retrieval Research10.4018/IJIRR.20160401026:2(24-40)Online publication date: 1-Apr-2016
https://dl.acm.org/doi/10.4018/IJIRR.2016040102
Ang JMirzal AHaron HHamed H(2016)Supervised, Unsupervised, and Semi-Supervised Feature SelectionIEEE/ACM Transactions on Computational Biology and Bioinformatics10.1109/TCBB.2015.247845413:5(971-989)Online publication date: 1-Sep-2016
https://dl.acm.org/doi/10.1109/TCBB.2015.2478454
Borkar PSarode MMalik L(2016)Employing Speeded Scaled Conjugate Gradient Algorithm for Multiple Contiguous Feature Vector FramesProcedia Computer Science10.1016/j.procs.2016.02.04778:C(740-747)Online publication date: 1-Mar-2016
https://dl.acm.org/doi/10.1016/j.procs.2016.02.047
Shao DZhang TMannar KHan Y(2016)Time Series Forecasting on Engineering Systems Using Recurrent Neural NetworksAdvanced Data Mining and Applications10.1007/978-3-319-49586-6_31(459-471)Online publication date: 12-Dec-2016
https://dl.acm.org/doi/10.1007/978-3-319-49586-6_31
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