A comparative study of redundant feature detection based feature selection methods

2014 International Conference on Computer, Information and Telecommunication Systems (CITS) ◽

10.1109/cits.2014.6878974 ◽

2014 ◽

Author(s):

Xue-Qiang Zeng ◽

Qian-Sheng Chen

Keyword(s):

Feature Selection ◽

Comparative Study ◽

Feature Detection ◽

Selection Methods ◽

Redundant Feature

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Comparative study on total nitrogen prediction in wastewater treatment plant and effect of various feature selection methods on machine learning algorithms performance

Journal of Water Process Engineering ◽

10.1016/j.jwpe.2021.102033 ◽

2021 ◽

Vol 41 ◽

pp. 102033

Author(s):

Faramarz Bagherzadeh ◽

Mohamad-Javad Mehrani ◽

Milad Basirifard ◽

Javad Roostaei

Keyword(s):

Machine Learning ◽

Feature Selection ◽

Wastewater Treatment ◽

Comparative Study ◽

Total Nitrogen ◽

Wastewater Treatment Plant ◽

Learning Algorithms ◽

Treatment Plant ◽

Machine Learning Algorithms ◽

Selection Methods

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Ranking Based Unsupervised Feature Selection Methods: An Empirical Comparative Study in High Dimensional Datasets

Advances in Soft Computing - Lecture Notes in Computer Science ◽

10.1007/978-3-030-04491-6_16 ◽

2018 ◽

pp. 205-218

Author(s):

Saúl Solorio-Fernández ◽

J. Ariel Carrasco-Ochoa ◽

José Fco. Martínez-Trinidad

Keyword(s):

Feature Selection ◽

Comparative Study ◽

High Dimensional ◽

Selection Methods ◽

Unsupervised Feature Selection ◽

High Dimensional Datasets

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Abstract 5118: Comparative study on feature selection methods in ovarian cancer diagnosis using chemometrics tools

10.1158/1538-7445.am2011-5118 ◽

2011 ◽

Author(s):

Seongkyu Yoon ◽

Hae Woo Lee ◽

Jay Liu ◽

Young Jung Na

Keyword(s):

Ovarian Cancer ◽

Feature Selection ◽

Comparative Study ◽

Cancer Diagnosis ◽

Selection Methods

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A comparative study of four feature selection methods for associative classifiers

2010 International Conference on Computer and Communication Technology (ICCCT) ◽

10.1109/iccct.2010.5640493 ◽

2010 ◽

Cited By ~ 1

Author(s):

Kavita Das ◽

O. P. Vyas

Keyword(s):

Feature Selection ◽

Comparative Study ◽

Selection Methods ◽

Associative Classifiers

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Comparative study of feature selection methods on microarray data

IEEE EMBS Asian-Pacific Conference on Biomedical Engineering, 2003. ◽

10.1109/apbme.2003.1302594 ◽

2004 ◽

Author(s):

T. Miyamoto ◽

S. Uchimura ◽

Y. Hamamoto ◽

N. Iizuka ◽

M. Oka ◽

...

Keyword(s):

Feature Selection ◽

Comparative Study ◽

Microarray Data ◽

Selection Methods

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A Comparative Study of Feature Selection Methods for the Discriminative Analysis of Temporal Lobe Epilepsy

Frontiers in Neurology ◽

10.3389/fneur.2017.00633 ◽

2017 ◽

Vol 8 ◽

Cited By ~ 8

Author(s):

Chunren Lai ◽

Shengwen Guo ◽

Lina Cheng ◽

Wensheng Wang

Keyword(s):

Feature Selection ◽

Comparative Study ◽

Temporal Lobe Epilepsy ◽

Temporal Lobe ◽

Selection Methods ◽

Discriminative Analysis

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A Comparative Study of Feature Selection Methods for Classification of Chest X-Ray Image as Normal or Abnormal Inside AWS ECS Cluster

2018 IEEE International Conference on Cloud Computing in Emerging Markets (CCEM) ◽

10.1109/ccem.2018.00011 ◽

2018 ◽

Author(s):

Vaibhav Sanjay Lalka ◽

Srinivasa Rao Kundeti ◽

Vinod Kumar ◽

Vijayananda J

Keyword(s):

Feature Selection ◽

Comparative Study ◽

Selection Methods ◽

X Ray ◽

Chest X Ray

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A Comparative Study of Feature Selection Methods for Biomarker Discovery

2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) ◽

10.1109/bibm.2018.8621267 ◽

2018 ◽

Cited By ~ 2

Author(s):

Zahra Mungloo-Dilmohamud ◽

Gary Marigliano ◽

Yasmina Jaufeerally-Fakim ◽

Carlos Pena-Reyes

Keyword(s):

Feature Selection ◽

Comparative Study ◽

Biomarker Discovery ◽

Selection Methods

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Feature selection methods for document clustering: a comparative study and a hybrid solution

International Journal of Data Analysis Techniques and Strategies ◽

10.1504/ijdats.2019.10022545 ◽

2019 ◽

Vol 11 (3) ◽

pp. 246

Author(s):

El Moukhtar Zemmouri ◽

Bouchra Frikh ◽

Brahim Ouhbi ◽

Asmaa Benghabrit ◽

Hicham Behja

Keyword(s):

Feature Selection ◽

Comparative Study ◽

Document Clustering ◽

Selection Methods ◽

Hybrid Solution

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A Comparative Study of Various Supervised Feature Selection Methods for Spam Classification

Proceedings of the Second International Conference on Information and Communication Technology for Competitive Strategies - ICTCS '16 ◽

10.1145/2905055.2905122 ◽

2016 ◽

Cited By ~ 5

Author(s):

Shrawan Kumar Trivedi ◽

Shubhamoy Dey

Keyword(s):

Feature Selection ◽

Comparative Study ◽

Selection Methods

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