Spectral feature selection for data mining

✍ Scribed by Zheng Alan Zhao, Huan Liu.

Publisher: CRC Press
Year: 2012.
Tongue: English
Leaves: 216
Series: Chapman & Hall/CRC data mining and knowledge discovery series.
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

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 Read more...

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.

✦ Table of Contents

Dedication......Page 6
Contents......Page 8
Preface......Page 12
Authors......Page 14
Symbol Description......Page 16
1. Data of High Dimensionality and Challenges......Page 18
2. Univariate Formulations for Spectral Feature Selection......Page 38
3. Multivariate Formulations......Page 72
4. Connections to Existing Algorithms......Page 100
5. Large-Scale Spectral Feature Selection......Page 126
6. Multi-Source Spectral Feature Selection......Page 160
References......Page 188

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