Gerasimov Roman

Inverse-based Lasso Regression: Novel Algorithms for Feature Selection and Multicollinearity Mitigation

Novel algorithms for estimating Lasso regression parameters by reformulating the problem as an inverse single-point optimization task are introduced, eliminating the need for explicit regularization parameter specification while maintaining robust feature selection capabilities and effective multicollinearity mitigatio...