Adaptive L1/2 Shooting Regularization Method for Survival Analysis Using Gene Expression Data
نویسندگان
چکیده
A new adaptive L₁/₂ shooting regularization method for variable selection based on the Cox's proportional hazards mode being proposed. This adaptive L₁/₂ shooting algorithm can be easily obtained by the optimization of a reweighed iterative series of L₁ penalties and a shooting strategy of L₁/₂ penalty. Simulation results based on high dimensional artificial data show that the adaptive L₁/₂ shooting regularization method can be more accurate for variable selection than Lasso and adaptive Lasso methods. The results from real gene expression dataset (DLBCL) also indicate that the L₁/₂ regularization method performs competitively.
منابع مشابه
A novel L1/2 regularization shooting method for Cox's proportional hazards model
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ورودعنوان ژورنال:
دوره 2013 شماره
صفحات -
تاریخ انتشار 2013