Adaptive L1/2 shooting regularization method for survival analysis using gene expression data Open Access

Author(s)
Date Issued
2013
Journal
ISSN
2356-6140
1537-744X
Citation
The Scientific World Journal , 2013,475702
DOI
URI
Type
Peer Reviewed Journal Article
Abstract
A new adaptive shooting regularization method for variable selection based on the Cox’s proportional hazards mode being proposed. This adaptive shooting algorithm can be easily obtained by the optimization of a reweighed iterative series of penalties and a shooting strategy of penalty. Simulation results based on high dimensional artificial data show that the adaptive 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 regularization method performs competitively.
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