Spectral Feature Selection for Data Mining

By: Contributor(s): Material type: ArticleArticleLanguage: English Publication details: Taylor & Francis 20120101ISBN:
  • b11426
Subject(s): Online resources: Summary: 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.
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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.

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