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Spectral feature selection for data mining
Author
Title
Spectral feature selection for data mining / Zheng Alan Zhao, Huan Liu.
ISBN
9781439862100
1439862109
9781439862094
1439862095
0429107196
9780429107191
1283596121
9781283596121
9786613908575
6613908576
9781138112629
1138112623
9781138112629
9781000023077
1000023079
Published
Boca Raton, FL : CRC Press, ©2012.
Physical Description
1 online resource (xv, 195 pages) : illustrations (some color)
Local Notes
Access is available to the Yale community.
Notes
English.
Access and use
Access restricted by licensing agreement.
Summary
Spectral Feature Selection for Data Mining introduces a novel feature selection technique that establishes a general platform for studying existing feature selection algorithms and developing new algorithms for emerging problems in real-world applications. This technique represents a unified framework for supervised, unsupervised, and semisupervised feature selection. The book explores the latest research achievements, sheds light on new research directions, and stimulates readers to make the next creative breakthroughs. It presents the intrinsic ideas behind spectral feature selection, its th.
Variant and related titles
O'Reilly Safari. OCLC KB.
Other formats
Print version: Zhao, Zheng (Zheng Alan). Spectral feature selection for data mining. Boca Raton, FL : CRC Press, 2012
Format
Books / Online
Language
English
Added to Catalog
October 31, 2023
Series
Chapman & Hall/CRC data mining and knowledge discovery series
Bibliography
Includes bibliographical references and index.
Contents
1. Data of high dimensionality and challenges
2. Univariate formulations for spectral feature selection
3. Multivariate formulations
4. Connections to existing algorithms
5. Large-scale spectral feature selection
6. Multi-source spectral feature selection.
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