Ontology highlight
ABSTRACT:
SUBMITTER: Huang HH
PROVIDER: S-EPMC4852916 | biostudies-literature | 2016
REPOSITORIES: biostudies-literature
Huang Hai-Hui HH Liu Xiao-Ying XY Liang Yong Y
PloS one 20160502 5
Cancer classification and feature (gene) selection plays an important role in knowledge discovery in genomic data. Although logistic regression is one of the most popular classification methods, it does not induce feature selection. In this paper, we presented a new hybrid L1/2 +2 regularization (HLR) function, a linear combination of L1/2 and L2 penalties, to select the relevant gene in the logistic regression. The HLR approach inherits some fascinating characteristics from L1/2 (sparsity) and ...[more]