Spectral Feature Selection for Data Mining
Download Url(s)
https://library.oapen.org/bitstream/20.500.12657/25274/1/1004820.pdf---
https://library.oapen.org/bitstream/20.500.12657/25274/1/1004820.pdf
---
https://library.oapen.org/bitstream/20.500.12657/25274/1/1004820.pdf
Author(s)
Zhao, Zheng Alan
Liu, Huan
Collection
Knowledge Unlatched (KU)Language
EnglishAbstract
This timely introduction to spectral feature selection illustrates the potential of this powerful dimensionality reduction technique in high-dimensional data processing. It presents the theoretical foundations of spectral feature selection, its connections to other algorithms, and its use in handling both large-scale data sets and small sample problems. 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. Source code for the algorithms is available online.
Keywords
Computer ScienceDOI
10.1201/b11426Publisher
Taylor & FrancisPublisher website
http://www.taylorandfrancis.com/Publication date and place
2012-01-01Grantor
Classification
Data mining