Clustering-Guided Sparse Structural Learning for Unsupervised Feature Selection

Many pattern analysis and data mining problems have witnessed high-dimensional data represented by a large number of features, which are often redundant and noisy. Feature selection is one main technique for dimensionality reduction that involves identifying a subset of the most useful features. In...

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Veröffentlicht in:IEEE transactions on knowledge and data engineering Jg. 26; H. 9; S. 2138 - 2150
Hauptverfasser: Li, Zechao, Liu, Jing, Yang, Yi, Zhou, Xiaofang, Lu, Hanqing
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.09.2014
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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ISSN:1041-4347, 1558-2191
Online-Zugang:Volltext
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