Sparse Elastic Net

A machine learning regression method combining L1 regularization (Lasso) and L2 regularization (Ridge). By performing sparse feature selection and handling multicollinearity, it achieves robust feature selection in high-dimensional, small-sample settings and is widely applied in bioinformatics and genomic data analysis.