Unsupervised feature selection for proportional data clustering via expectation propagation

The 2013 International Joint Conference on Neural Networks (IJCNN) ◽

10.1109/ijcnn.2013.6706757 ◽

2013 ◽

Author(s):

Wentao Fan ◽

Nizar Bouguila

Keyword(s):

Feature Selection ◽

Data Clustering ◽

Expectation Propagation ◽

Unsupervised Feature Selection ◽

Proportional Data ◽

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An Unsupervised, Fast Correlation-Based Filter for Feature Selection for Data Clustering

Lecture Notes in Electrical Engineering - Proceedings of the First International Conference on Advanced Data and Information Engineering (DaEng-2013) ◽

10.1007/978-981-4585-18-7_10 ◽

2013 ◽

pp. 87-94 ◽

Author(s):

Part Pramokchon ◽

Punpiti Piamsa-nga

Keyword(s):

Feature Selection ◽

Data Clustering ◽

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Unsupervised Feature Selection for Multi-cluster Data via Smooth Distributed Score

Communications in Computer and Information Science - Emerging Intelligent Computing Technology and Applications ◽

10.1007/978-3-642-31837-5_11 ◽

2012 ◽

pp. 74-79 ◽

Author(s):

Furui Liu ◽

Xiyan Liu

Keyword(s):

Feature Selection ◽

Unsupervised Feature Selection ◽

Cluster Data ◽

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UFSSF - An Efficient Unsupervised Feature Selection for Streaming Features

Advances in Knowledge Discovery and Data Mining - Lecture Notes in Computer Science ◽

10.1007/978-3-319-93037-4_39 ◽

2018 ◽

pp. 495-507

Author(s):

Naif Almusallam ◽

Zahir Tari ◽

Jeffrey Chan ◽

Adil AlHarthi

Keyword(s):

Feature Selection ◽

Unsupervised Feature Selection ◽

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Efficient unsupervised feature selection for sparse data

2011 IEEE EUROCON - International Conference on Computer as a Tool ◽

10.1109/eurocon.2011.5929185 ◽

2011 ◽

Author(s):

A. Ferreira ◽

M. Figueiredo

Keyword(s):

Feature Selection ◽

Sparse Data ◽

Unsupervised Feature Selection ◽

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An Information-theoretic Approach to Unsupervised Feature Selection for High-Dimensional Data

10.3390/ecea-5-06697 ◽

2019 ◽

Author(s):

Shao-Lun Huang

Keyword(s):

Feature Selection ◽

High Dimensional Data ◽

High Dimensional ◽

Theoretic Approach ◽

Unsupervised Feature Selection ◽

Information Theoretic ◽

Selection For ◽

Information Theoretic Approach

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Unsupervised Feature Selection for Text Data

Lecture Notes in Computer Science - Advances in Case-Based Reasoning ◽

10.1007/11805816_26 ◽

2006 ◽

pp. 340-354 ◽

Author(s):

Nirmalie Wiratunga ◽

Rob Lothian ◽

Stewart Massie

Keyword(s):

Feature Selection ◽

Text Data ◽

Unsupervised Feature Selection ◽

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Hybrid fast unsupervised feature selection for high-dimensional data

Expert Systems with Applications ◽

10.1016/j.eswa.2019.01.016 ◽

2019 ◽

Vol 124 ◽

pp. 97-118 ◽

Author(s):

Zhaleh Manbari ◽

Fardin AkhlaghianTab ◽

Chiman Salavati

Keyword(s):

Feature Selection ◽

High Dimensional Data ◽

High Dimensional ◽

Unsupervised Feature Selection ◽

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Unsupervised Feature Selection for Multi-View Clustering on Text-Image Web News Data

Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management - CIKM '14 ◽

10.1145/2661829.2661993 ◽

2014 ◽

Author(s):

Mingjie Qian ◽

Chengxiang Zhai

Keyword(s):

Feature Selection ◽

Unsupervised Feature Selection ◽

Selection For ◽

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Unsupervised Feature Selection for Biomarker Identification in Chromatography and Gene Expression Data

Artificial Neural Networks in Pattern Recognition - Lecture Notes in Computer Science ◽

10.1007/11829898_25 ◽

2006 ◽

pp. 274-285 ◽

Author(s):

Marc Strickert ◽

Nese Sreenivasulu ◽

Silke Peterek ◽

Winfriede Weschke ◽

Hans-Peter Mock ◽

...

Keyword(s):

Gene Expression ◽

Feature Selection ◽

Gene Expression Data ◽

Expression Data ◽

Unsupervised Feature Selection ◽

Biomarker Identification ◽

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Unsupervised feature selection for principal components analysis

Proceeding of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD 08 ◽

10.1145/1401890.1401903 ◽

2008 ◽

Author(s):

Christos Boutsidis ◽

Michael W. Mahoney ◽

Petros Drineas

Keyword(s):

Feature Selection ◽

Principal Components Analysis ◽

Principal Components ◽

Unsupervised Feature Selection ◽

Components Analysis ◽

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