Feature Selection and Cancer Classification via Sparse Logistic Regression with the Hybrid L1/2 +2 Regularization

Open Access

Peer-reviewed

Research Article

Feature Selection and Cancer Classification via Sparse Logistic Regression with the Hybrid L_{1/2 +2} Regularization

Hai-Hui Huang,

Affiliation Faculty of Information Technology & State Key Laboratory of Quality Research in Chinese Medicines, Macau University of Science and Technology, Avenida Wai Long, Taipa, Macau, 999078, China
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Xiao-Ying Liu,

Affiliation Faculty of Information Technology & State Key Laboratory of Quality Research in Chinese Medicines, Macau University of Science and Technology, Avenida Wai Long, Taipa, Macau, 999078, China
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Yong Liang

* E-mail: yliang@must.edu.mo

Affiliation Faculty of Information Technology & State Key Laboratory of Quality Research in Chinese Medicines, Macau University of Science and Technology, Avenida Wai Long, Taipa, Macau, 999078, China
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Lung and intrathoracic tumors
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Prostate gland
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Lymphoma
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Gene expression
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Adenocarcinoma of the lung
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Simulation and modeling
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Algorithms
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Prostate cancer
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