Revisiting Logistic Regression for High-Dimensional Gene Expression Data
A reformulated logistic regression framework designed for feature selection and classification in complex high-dimensional settings is proposed and several selected features were consistent with previously reported disease-associated markers, supporting the biological plausibility of the model.