Analyzing Robustness of Boruta Feature Selection in a Univariate Framework

Poster Session I

Keyword: Other

Abstract: 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.

• Priyanka Paul (Presenting Author)
• Timothy Brick (Author)
• Andreas Brandmaier (Author)