Abstract
Nowadays, a series of methods are based on a L 1 penalty to solve the variable selection problem for a Cox’s proportional hazards model. In 2010, Xu et al. have proposed a L 1/2 regularization and proved that the L 1/2 penalty is sparser than the L 1 penalty in linear regression models. In this paper, we propose a novel shooting method for the L 1/2 regularization and apply it on the Cox model for variable selection. The experimental results based on comprehensive simulation studies, real Primary Biliary Cirrhosis and diffuse large B cell lymphoma datasets show that the L 1/2 regularization shooting method performs competitively.
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Acknowledgments
This work was supported by the Macau Science and Technology Develop Funds (Grant No. 017/2010/A2) of Macau SAR of China and the National Natural Science Foundation of China (Grant No. 11171272).
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Communicated by G. Acampora.
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Luan, XZ., Liang, Y., Liu, C. et al. A novel L1/2 regularization shooting method for Cox’s proportional hazards model. Soft Comput 18, 143–152 (2014). https://doi.org/10.1007/s00500-013-1042-6
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DOI: https://doi.org/10.1007/s00500-013-1042-6