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Multinomial regression with elastic net penalty and its grouping effect in gene selection. (English) Zbl 1468.62304

Summary: For the multiclass classification problem of microarray data, a new optimization model named multinomial regression with the elastic net penalty was proposed in this paper. By combining the multinomial likeliyhood loss and the multiclass elastic net penalty, the optimization model was constructed, which was proved to encourage a grouping effect in gene selection for multiclass classification.

MSC:

62H30 Classification and discrimination; cluster analysis (statistical aspects)
62P10 Applications of statistics to biology and medical sciences; meta analysis
90C90 Applications of mathematical programming

Software:

vbmp; glmnet
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References:

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