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...
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| Formaat: | Elektronisch Hoofdstuk |
| Taal: | Engels |
| Gepubliceerd in: |
Taylor & Francis
2012
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| Online toegang: | DOAB: download the publication DOAB: description of the publication |
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| 100 | 1 | |a Zhao, Zheng Alan |4 auth | |
| 700 | 1 | |a Liu, Huan |4 auth | |
| 245 | 1 | 0 | |a Spectral Feature Selection for Data Mining |
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| 520 | |a 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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| 546 | |a English | ||
| 650 | 7 | |a Data mining |2 bicssc | |
| 653 | |a Computer Science | ||
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