A Stable Lasso
The Stable Lasso improves variable selection stability for Lasso when predictors are correlated. It achieves this by integrating a weighting scheme into the penalty function, where weights increase based on a correlation-adjusted ranking of predictors' predictive power. Empirical tests show it significantly outperforms standard Lasso and other methods in both simulated and real-world datasets.