Spectral Feature Selection for Data Mining:
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 handlin...
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Taylor and Francis
2012
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| Online-Zugang: | kostenfrei |
| Zusammenfassung: | 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 |
| Beschreibung: | 1 Online-Ressource |
| ISBN: | 9781439862094 |
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| id | DE-604.BV046929214 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T15:34:04Z |
| indexdate | 2025-01-23T23:01:23Z |
| institution | BVB |
| isbn | 9781439862094 |
| language | English |
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| publishDate | 2012 |
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| publisher | Taylor and Francis |
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| spelling | Liu, Huan aut Spectral Feature Selection for Data Mining Taylor and Francis 2012 1 Online-Ressource txt rdacontent c rdamedia cr rdacarrier 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 Zhao, Zheng Alan aut https://www.doabooks.org/doab?func=search&query=rid:32882 Verlag kostenfrei Volltext |
| spellingShingle | Liu, Huan Zhao, Zheng Alan Spectral Feature Selection for Data Mining |
| title | Spectral Feature Selection for Data Mining |
| title_auth | Spectral Feature Selection for Data Mining |
| title_exact_search | Spectral Feature Selection for Data Mining |
| title_exact_search_txtP | Spectral Feature Selection for Data Mining |
| title_full | Spectral Feature Selection for Data Mining |
| title_fullStr | Spectral Feature Selection for Data Mining |
| title_full_unstemmed | Spectral Feature Selection for Data Mining |
| title_short | Spectral Feature Selection for Data Mining |
| title_sort | spectral feature selection for data mining |
| url | https://www.doabooks.org/doab?func=search&query=rid:32882 |
| work_keys_str_mv | AT liuhuan spectralfeatureselectionfordatamining AT zhaozhengalan spectralfeatureselectionfordatamining |