Analyzing Robustness of Boruta Feature Selection in a Univariate Framework

In psychological science, dealing with large datasets having a multitude of features or variables from various modalities is common. In empirical modeling while theoretical foundations guide variable selection, an inductive, data-driven approach like Boruta feature selection can leverage empirical data and allow for informed decision making and support theory development.