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Spectral Feature Selection for Data Mining
Zheng Alan Zhao and Huan Liu
2011
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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 semisupervise
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Keywords
- Computer Nodes
- Data mining
- Data set
- Dimensionality Reduction
- Existing Feature Selection
- F1 F2 F3 F4 F5
- F2 F3 F4 F5 F6
- feature extraction
- feature selection
- Feature Selection Algorithms
- Feature Selection Techniques
- Fisher Score
- Gene Selection
- high-dimensional data processing
- Laplacian matrix
- LDA
- Machine learning
- microRNA Microarray
- Multivariate Formulations
- Normalized Laplacian Matrix
- rank aggregation
- Redundant Features
- similarity matrix
- Spectral Feature Selection
- TIMP Metallopeptidase Inhibitor
Links
DOI: 10.1201/b11426Editions