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Joint L(1/2)-Norm Constraint and Graph-Laplacian PCA Method for Feature Extraction
Principal Component Analysis (PCA) as a tool for dimensionality reduction is widely used in many areas. In the area of bioinformatics, each involved variable corresponds to a specific gene. In order to improve the robustness of PCA-based method, this paper proposes a novel graph-Laplacian PCA algori...
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| Veröffentlicht in: | Biomed Res Int |
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| Hauptverfasser: | , , , , , |
| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
Hindawi
2017
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| Schlagworte: | |
| Online Zugang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5392409/ https://ncbi.nlm.nih.gov/pubmed/28470011 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1155/2017/5073427 |
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