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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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Bibliographische Detailangaben
Veröffentlicht in:Biomed Res Int
Hauptverfasser: Feng, Chun-Mei, Gao, Ying-Lian, Liu, Jin-Xing, Wang, Juan, Wang, Dong-Qin, Wen, Chang-Gang
Format: Artigo
Sprache:Inglês
Veröffentlicht: Hindawi 2017
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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