The Impact of the L1/L2 Ratio on Selection Stability and Solution Sparsity along the Elastic Net Regularization Path in High-Dimensional Genomic Data

High-dimensional genomic datasets (p>n) pose persistent challenges for predictive modeling and biomarker-oriented feature selection due to multicollinearity and instability of selected feature sets under resampling. Although Elastic Net is widely used to address correlated predictors via combined L1...

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Detalles Bibliográficos

Principais autores:	Fani Fahira, Kusman Sadik, Cici Suhaeni, Agus M Soleh
Formato:	Artigo
Idioma:	Inglês
Publicado:	Politeknik Negeri Batam 2026-02-01
Series:	Journal of Applied Informatics and Computing
Assuntos:	elastic net lasso high-dimensional data feature selection stability sparsity regularization path
Acceso en liña:	https://jurnal.polibatam.ac.id/index.php/JAIC/article/view/12059
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