Spectral Feature Selection for Data Mining

Huan Liu author Zheng Alan Zhao author

Format:Hardback

Publisher:Taylor & Francis Inc

Published:14th Dec '11

Currently unavailable, and unfortunately no date known when it will be back

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Spectral Feature Selection for Data Mining cover

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 theoretical foundations, its connections to other algorithms, and its use in handling both large-scale data sets and small sample problems. The authors also cover feature selection and feature extraction, including basic concepts, popular existing algorithms, and applications.

A timely introduction to spectral feature selection, this book illustrates the potential of this powerful dimensionality reduction technique in high-dimensional data processing. Readers learn how to use spectral feature selection to solve challenging problems in real-life applications and discover how general feature selection and extraction are connected to spectral feature selection.

ISBN: 9781439862094

Dimensions: unknown

Weight: 521g

220 pages